The three-axis stabilization geostationary remote sensing satellite features high time resolution and plays a significant role in weather forecasting and environmental monitoring. With the future development of satellite technology, we propose a rapid geolocation algorithm for three-axis stabilization geostationary remote sensing satellites from the perspective of software algorithms. The method assesses conventional remote sensing data geolocation methods and the coordination group for meteorological satellites (CGMS, Coordination Group for Meteorological Satellites) nominal grid publishing format. First, the initial incident viewing vector of each detector on the sensor was constructed. Then, by reflecting the satellite platform's east-west and north-south mirrors, the outgoing vector of the payload coordinate system was obtained. This vector was converted to the satellite body coordinate system and, subsequently, to the satellite orbit coordinate system. The conversion of the earth-fixed coordinate system and the mirror rotation angle under ideal CGMS grid conditions were obtained, and the mirror rotation angle was converted to the corresponding CGMS nominal grid position to complete data positioning. The algorithm omits the complex process of calculating the intersection point between the viewing vector and the geodetic ellipsoid sphere from the earth-fixed coordinate system, resulting in an 83.3% improvement in computational efficiency without compromising positioning accuracy compared with conventional geolocation methods. This algorithm greatly improves the processing efficiency of geostationary meteorological satellite positioning, but its limitation is that the data processing results must be released in the CGMS nominal grid format.

Soil nitrite (NO2‒) is an important reactive intermediate in many nitrogen transformation processes, but it is unstable under acidic conditions. Canonical extraction method of soil NO2‒ with potassium chloride (KCl) solution greatly underestimates its concentration. In order to reflect the concentration more accurately, we optimized the extraction method of soil NO2‒ in this study. Moreover, soil ammonium (NH4+) and nitrate (NO3‒) were also systematically investigated to achieve efficient extraction of soil inorganic nitrogen. The results showed that un-buffered KCl significantly underestimated soil NO2‒ concentration compared to DIW. The highest recovery of NO2‒ was obtained by extracting with DIW at 10 min of oscillation for three soils. Compared with DIW, the concentration of NH4+ and NO3‒ in soil extracted from KCl solution increased significantly. Furthermore, the soil inorganic nitrogen content of extracts stored at 4°C for one day were closer to directly measurements of fresh samples than the other storage methods. Overall, the recommend analysis method for soil NO2‒ was extracted by DIW, oscillated for 10 min, and filtered by a 0.45 µm filter, and soil NH4+ and NO3‒ were extracted with KCl solution and oscillated for 30 min. The extract should be stored at 4°C and analyzed within 24 hours.

The overuse of chemical fertilisers degrades the soil ecosystem and restricts the natural development of plants. Within the coffee industry, various by-products are produced throughout the process of coffee production and consumption, which are significant in terms of environmental waste. SCG (spent coffee grounds) contain a variety of bioactive compounds that have demonstrated potential applications in various fields. These compounds can enhance soil quality by improving its chemical, physicochemical, physical properties, and biological fertility, ultimately leading to improved plant growth. This study examines the impact of SCG, vermicompost, and chemical fertilisers on the growth of organic red radish (Ravanello Cherry Belle) and soil quality. The experiment, conducted in a greenhouse, tested various concentrations and applications of SCG. Results showed that the SCGT 0.5 gm treatment yielded the highest mean plant length (18.47 cm) and fresh weight (27.54 grammes), while the SCG 10% treatment resulted in the lowest mean plant length (4.54 cm) and fresh weight (0.07 grammes). Vermicompost at 50% concentration produced the highest mean leaf surface area (58.32). These findings suggest the potential of SCG as a sustainable fertiliser alternative, contributing to improved plant growth and soil quality, thus supporting sustainable agricultural practices and a circular economy.

In this study, the effects of food waste (FW) compost, vermicompost, and chemical fertilizers on the growth of organic red radish and soil quality are investigated to promote sustainable agriculture. Utilizing a comparative approach, it assesses the impacts of these fertilizers on various plant growth metrics and soil characteristics, highlighting the potential of converting FW into nutrient-rich amendments as a sustainable alternative to chemical fertilizers. The results indicate a significant variation in fresh weight among different treatments. For example, the FV 25% treatment demonstrated a relatively high mean fresh weight of 7.9664, while the CO 50% treatment yielded a much lower mean fresh weight of 0.2589. These numbers underscore the potential efficacy of specific FW treatments in enhancing plant growth, with VC 50% and FV 25% showing considerable promise in increasing crop yield. The study concludes that FW compost and vermicompost significantly enhance plant growth and soil quality, advocating for their use as sustainable and environmentally friendly alternatives to chemical fertilizers. The findings emphasize the importance of selecting appropriate fertilizer types and concentrations to optimize agricultural productivity and environmental sustainability, supporting the incorporation of FW into agricultural systems as a beneficial resource.

This study explores the application of the Fully Convolutional Network (FCN) algorithm to the field of meteorology, specifically for the short-term nowcasting of severe convective weather events such as hail, convective wind gust (CG) and thunderstorms, short-term heavy rain(STHR) in Gansu. Training data comes from the European Center for Medium-Range Weather Forecasts (ECMWF) and real-time ground observations, the performance of the proposed FCN model based on 2017 to 2021 training datasets demonstrate a high prediction accuracy, with an overall error rate of 16.6%. Furthermore, the model exhibited an error rate of 18.6% across both severe and non-severe weather conditions when testing against the 2022 dataset. Operational deployment in 2023 has yielded an average Critical Success Index (CSI) of 24.3%, a Probability of Detection (POD) of 62.6%, and a False Alarm Ratio (FAR) of 71.2% for these convective events. It is noteworthy that the predicting performance for STHR was particularly effective with the highest POD and CSI, as well as the lowest FAR. CG and hail predictions had comparable CSI and FAR scores, although the POD for CG surpassed that for hail. The FCN model’s optimal performance for hail prediction occurred at the 4th, 8th, and 10th forecast hours, while for CG, the 6th hour was most accurate, and for STHR, the 2nd and 4th hours were most effective. These findings underscore the FCN model's ideal suitability for short-term forecasting of severe convective weather, presenting extensive prospects for the automation of meteorological operations in the future.

Ecological stoichiometry is an important index to reflect ecological interaction and the balance of various elements in ecological processes. At present, the stoichiometric spatial distribution of soil carbon (C), nitrogen (N), phosphorus (P) and potassium (K) in farmland and grassland of Inner Mongolia and its influencing factors are still unclear. In this study, the spatial distribution of soil nutrient content and stoichiometry and the effects of environmental factors on soil C:N:P:K stoichiometry were analyzed under different land use patterns in four agro-pastoral areas. The results showed that there was a geographical gradient in the ecological stoichiometric relationship between farmland and grassland. RCN, RCP, RCK, RNP and RNK showed an "N" distribution from west to east, while RPK showed a "V" distribution. The difference in spatial distribution was more significant than the difference in land use pattern. The ecological stoichiometric relationship of grassland was mainly affected by the content of C and N, and was related to the similarity of soil properties. The field ecological stoichiometry was mainly affected by the content of nitrogen and phosphorus, and had a great relationship with fertilization. The effects of MAT and MAP on soil ecological stoichiometry were related to the inter-regional environmental heterogeneity. The influence of MAP on farmland and MAT on grassland was more significant. It was of great significance for field management according to local conditions, rational utilization of land resources and sustainable development of agriculture to clarify the ecological stoichiometric characteristics of farmland and grassland in agro-pastoral ecotone.

Despite widespread industrial use, the environmental safety of Hydroquinone (HQ), a benzene compound from plants used in processes like cosmetics, remains uncertain. This study evaluated the ecotoxicological impact of HQ on soil and river environments, utilizing non-target indicator organisms from diverse trophic levels: Daphnia magna, Vibrio fischeri, Allium cepa, and Eisenia fetida. For a more environmentally realistic assessment, microbial communities from a river and un-treated soil underwent 16S rRNA gene sequencing, with growth and changes in community-level physiological profiling assessed using Biolog EcoPlate™ assays. The water indicator D. magna exhibited the highest sensitivity to HQ (EC50 = 0.142 µg/mL), followed by V. fischeri (EC50 = 1.446 µg/mL), and A. cepa (LC50 = 7.631 µg/mL), while E. fetida showed the highest resistance (EC50 = 234 mg/Kg). Remarkably, microbial communities mitigated HQ impact in both aquatic and terrestrial environments. River microorganisms displayed minimal inhibition, except for a significant re-duction in polymer metabolism at the highest concentration (100 µg/mL). Soil communities demonstrated resilience up to 100 µg/mL, beyond which there was a significant decrease in population growth and the capacity to metabolize carbohydrates and polymers. Despite microbial mitigation, HQ remains highly toxic to various trophic levels, emphasizing the necessity for en-vironmental regulations.

Rational delineation of urban–rural boundaries is a foundational prerequisite for holistic urban and rural development planning and rational resource allocation. However, the results of division of urban–rural boundaries extracted using a single data source are non-comprehensive. To address this problem, the present study proposes a method for using multiple sources such as population data, nighttime light data, land use, and points of interest (POI) data to extract urban–rural boundaries. Considering Guizhou Province for a case study, we here present a two-step method for identifying urban–rural boundaries. First, the random forest model was combined with the dasymetric mapping method to obtain the population spatialization data with a 30-m resolution in the studied province. Second, using the breaking point method, we extracted the urban–rural boundary for Guizhou Province in 2020 based on the spatialized population. This method fully integrated the benefits of various data and judiciously extracted the boundaries of the main urban areas and small- and medium-sized towns of each city in the study province at the same spatial scale. The stratified random sampling method revealed that the average overall accuracy was 88.05%. The method proposed has certain universality and application value and allows identifying the urban–rural boundaries more accurately and practically.

To study the oil and gas distribution law in the slope area of the hydrocarbon-bearing basin, the distribution of the effective dominant path of sand bodies transporting oil and gas is a fundamental subject. In this paper, we introduced an effective way to predict such transport paths and applied the method to study the sand bodies of the lower first member of the Shahejie Formation (E3s1L) in the southern area of the Qikou Depression in the Bohai Bay Basin (Qinan). We first define the dominant hydrocarbon transport paths of the sand body as the superimposed area of the contiguously distributed area of the sand body and the paleotectonic ridges at the top of the formation where the sand body is located. Then we define the oil and gas supply area of the oil source fault as the overlapped area of the favorable transport path of oil source faults and the width of the associated fracture zone. Stacking the two areas, we can delineate the distribution of the effective dominant transport paths of the sand bodies. The results from our case study of the Qinan area show that the effective dominant paths of sand bodies transporting oil and gas in the E3s1L Formation in the Qinan area are distributed throughout the region with better development in the west than in the east. The paths in the eastern part extend from north to south, while the paths in the western part extend from northeast to southwest, which is favorable for the convergence of oil and gas generated from the source rocks of the third member of Shahejie Formation (Es3) in the Northeastern main depression of Qikou and the formation of oil and gas accumulations in the l E3s1L Formation. The results are consistent with the fact that oil and gas discovered in the E3s1L Formation in the Qinan region are mainly distributed in the central and western regions, with a small amount in the southeast. Therefore, the suggested method is feasible to predict the effective dominant path of sand bodies transporting oil and gas.

Abstract: Wildfires in forest ecosystems exert substantial ecological, economic, and social impacts. The effectiveness of fire management hinges on precise pre‐fire risk assessments to inform mitigation efforts. This study aims to investigate the relationship between predictions from pre‐fire risk assessments and outcomes observed through post‐fire burn severity analyses. In this study, forest fire risk was assessed with the Fuzzy Analytical Hierarchy Process, in which fire behavior factors were used as input. The degree of burn was determined using the Random Forest method using 11519 training points and 400 test points on Sentinel‐2 satellite images in three different classes. According to the results obtained from 266 selected test points located within the forest boundaries, all primary factors showed an increased effect in areas with high burn severity. Climate, in particular, emerged as the most influential factor, accounting for 52% of the overall impact. However, in cases of high fire severity, climate proved to be the most effective risk factor, ac‐counting for 67%. It followed by topography with 50% accuracy at high fire intensity. In the risk assessment is based on the FAHP method, climate was assigned the highest weight value among other factors with 32.2%. Topography emerged as the second most effective risk factor with 27 %. To evaluate the results more comprehensively both visually and statistically, two regions with different stand canopy characteristics were selected within the study area. While high burn severity had the highest accuracy in Case 1 area, moderate burn severity had the highest in Case 2 area. During the days when the fire continued, the direction of spread was obtained from MODIS images. In this way, the fire severity depending on the direction of fire progression was also interpreted. Through an analysis of various case studies and existing literature, the research underscores both the strengths and limitations inherent in predicting forest fire behavior‐based pre‐fire risk assessments. Furthermore, it emphasizes the necessity of continuous improvement to increase the success of forest fire management.

Jamoytius kerwoodi, is a primitive, eel-like jawless vertebrate found uniquely in an Early Silurian (Llandovery epoch; 444-433 Ma) horizon near Lesmahagow, Scotland. This species is a rare component of a low-diversity dominantly nektonic detritus and herbivorous fauna living over an anoxic bottom and is found at the transition from a marine-influenced, probably brackish-water, deep-water basin to a shallower-water, less saline and likely freshwater basin. In the absence of true teeth, Jamoytius was probably a detritivore or herbivore feeding on Ceratiocaris. Jamoytius may be a direct ancestor of living lampreys, especially as their ectoparasitic mode of life might have evolved from ancestral microphagous filterers or herbivores.

The exposure of Mediterranean forests to large wildfires requires mechanisms to prevent and mitigate their negative effects on the territory and ecosystems. Fuel models synthesize the complexity and heterogeneity of forest fuels and allow understanding and modelling of fire behavior. However, it is sometimes challenging to define the fuel type in a structurally heterogeneous forest stand due to the mixture of characteristics from different types and limitations of qualitative field observation and passive and active airborne remote sensing. This can impact the performance of classification models that rely on in situ identification of fuel type as ground-truth, which can lead to a mistaken prediction of fuel types over larger areas in fire prediction models. In this study, a handheld mobile laser scanner (HMLS) system were used to assess its capability to define Prometheus fuel types in 43 forest plots in Aragón (NE Spain). The HMLS system captured the vertical and horizontal distribution of fuel at extremely high resolution to derive high-density three-dimensional point clouds (average: 63,148 points/m2) which were discretized into voxels of 0.05 m3. The total number of voxels in each 5 cm height stratum was calculated to quantify the fuel volume in each stratum, providing the vertical distribution of fuels (m3/m2) for each plot at centimetric scale. Additionally, fuel volume was computed for each Prometheus height stratum (0.60, 2, and 4 m) for each plot. The Prometheus fuel types were satisfactory identified for each plot, which was compared with the fuel type estimated in the field. This led to the modification of the ground-truth in 10 out of the 43 plots, with estimation errors between types 2–3, 5–6, and 6–7. These results demonstrate the ability of HMLS systems to capture fuel heterogeneity at centimetric scales for the definition of fuel types in Mediterranean forests, making them powerful tools for fuel mapping and fire modelling, and ultimately for improving wildfire prevention and forest management.

The increasing importance of batteries in the 21st century and the challenges posed by the anticipated growth in end-of-life batteries, particularly in Europe, are addressed. Projections indicate a significant increase in battery waste, with a specific focus on the recycling of black mass (BM)—a complex and hazardous byproduct of the battery recycling process. The research employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to systematically analyze the hazardousness of BM derived from various types of batteries. The findings reveal the inherently hazardous nature of BM, classifying it under multiple hazardous properties (HPs) according to European regulations. The urgent need for a definitive legislative classification of the hazardousness of BM is emphasized, and the potential of innovative technologies and strategies to improve recycling performance while mitigating risks is highlighted. The research significantly contributes to understanding the complexities of BM recycling, providing a foundation for future advancements in this area and emphasizing the need for further exploration and economic feasibility analysis of recycling technologies.

The amount and composition of litter was evaluated, during May and June 2021, at two urban beaches, i.e. La Victoria and La Cortadura, in Cadiz, SW Spain. Surveys were daily carried out in the morning and in the evening during the week−ends to quantify the daily accumulation of beach litter and relate it with the number of beach users, which was assessed at around 1:00 p.m. Litter amount was also related to clean-up operations that very mechanically and manually carried out each day very early in the morning. A total of 8108 items were collected at the two investigated sectors during the study period and beach visitors were quantified in each one of 22 surveys. Plastic was the most common material representing 82% in La Victoria and 68% in La Cortadura. The most common items were cigarette butts and small hard plastic fragments. Some hazardous litter items for beach visitors were identified such as broken glass. The number of visitors has been positively related to the amount of litter. Significant differences were seen in the litter abundance between the morning and afternoon assessments since the beaches are daily cleaned and show bins to facilitate litter disposal. Cleaning operations remove much of the litter items but always leave low quantities of small items uncollected. Efforts to prevent litter on these beaches should focus on informing visitors properly in order to avoid dumping and on improving clean-up operations.

Triclopyr is an auxin-like herbicide extensively employed to manage weeds in food crops and pastures. Triclopyr has been detected in environmental matrices, with a notable presence within aquatic ecosystems. Given the limited understanding of its fate in the environment, potential implications for environmental and human health, and the lack of adequate monitoring in various environmental compartments, triclopyr is now considered a contaminant of emerging concern (CEC). The present study was undertaken to investigate the impact of triclopyr on zebrafish development, with a specific focus on assessing its embryotoxic, behavioral, and neurotoxic effects at environmentally realistic concentrations ranging from 0.5 to 50 µM on zebrafish embryos. Our results revealed that triclopyr caused sublethal effects on zebrafish embryos, such as delayed hatchability at 50 µM, yolk sac retention at 0.5, 1, 5, and 10 µM, and uninflated swim bladder at 50 µM concentration of triclopyr. Moreover, a subtle alteration in the swimming activity of larvae was observed in the 10 µM triclopyr after 144 hours of exposure. However, the activity of acetylcholinesterase, remained unchanged after triclopyr exposure. Taken together, these comprehensive findings suggest that triclopyr can induce adverse effects on the early development of zebrafish, even at concentrations detected in aquatic environments.

Generating early warning signals of reduced resilience in ecosystems is crucial for conservation and management endeavors. However, the practical implications of such early warning signal systems are still limited by the lack of data and uncertainties associated with predicting complex systems such as ecosystems. This research aims to investigate the feasibility of developing an early warning system capable of identifying an upcoming critical transition within mangrove forest ecosystems. Using time series analysis of remote sensing images, the resilience of mangrove forests was explored across two distinct study sites. One site (Qeshm Island) has been adversely affected by land-use and land-cover changes, while the other (Gabrik) serves as a reference ecosystem. The study uses data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite to quantify three remotely sensed indices: the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI), and the Modified Vegetation Water Ratio (MVWR). In addition, Landsat data has been used to explore temporal alterations in land-use and land cover. To identify early warning signals, indicators such as autocorrelation (acf(1)), standard deviation (SD), and skewness (SK) are applied. The findings indicate a signal of reduced resilience by a significant increase in NDVI statistical metrics (acf(1): 0.50, SD: 0.9). Although MNDWI showed significant early warning signals in Qeshm Island (acf(1); 0.86, SD: 0.90), it provided a false alarm in the reference study site. MVWR failed to generate early warning signals of reduced resilience (acf(1); -0.100, SD: -0.07, SK: -0.21). Land-use land-cover change may explain reduced resilience in the forests. This study not only emphasizes the potential of remote sensing in monitoring the state of mangrove forests but also contributes to advancing our understanding of ecosystem dynamics. The findings of this study can be integrated with ecosystem management tools to enhance the effectiveness of conservation efforts aimed at safeguarding mangroves. This is the first report of the successful application of remote sensing in generating early warning signals of reduced resilience within mangrove forests in the Middle East.

This study concerns in to collect, via a systematic review, works from international academics that employed bicycles to collect primary data on environmental variables for research on microclimatic thermal problems in urban contexts. To that purpose, a systematic review was con-ducted employing several important processes that favor the collecting of relevant material from three well-regarded worldwide academic platforms using well-defined keywords. A selection of papers identified through the platforms was produced, and after reading the titles, abstracts, and entire works, 13 articles were collected that employed bicycles in their mobile transects between 2011 and 2023. The analytical methodologies connected to the thermal environment employed by the research, such as the primary characterizers of urban morphology, were visible from this. The systematic review showed effective in attempting to comprehend current research in the scientific community that employed the approach of mobile measurements using bicycles. The great bulk of work was done in the Northern Hemisphere, specifically on the European continent. Furthermore, it was discovered that the number of publications published using this approach has increased in the previous two years. It is worth emphasizing that, while the platforms offer outstanding results in terms of article discovery, we are nevertheless aware of additional publications that employed similar technique but did not appear in the platforms' results. More study utilizing the bicycle is anticipated for, so that the process may be improved and the precision of future results can be reached.

Slave Province in Canada is an Archean granite-supracrustal terrane at the northwestern corner of the Canadian Shield. It is bordered by the Thelon–Taltson orogen (2.0 to 1.9 Ga) to the south-east and the Wopmay orogen (1.9 to 1.8 Ga) to the west. Acasta gneisses exposed in the western-most Slave province and the Wopmay rocks close to the gneisses were collected systematically for K-Ar and laser step-heating 40Ar /39Ar analyses of the biotite and amphibole. The K-Ar biotite ag-es of the four Wopmay samples range from 1816 ± 18 Ma to 1854 ± 26 Ma, which is within the reported U-Pb zircon age range of the Wopmay orogen. The K-Ar biotite ages of the fifteen Acasta gneisses range from 1779 ± 25 Ma to 1877 ± 26 Ma, except for a younger sample (1711 ± 25 Ma). The 40Ar/39Ar biotite analyses of the three samples from the Wopmay orogen give the plateau ages of 1826 ± 21 Ma, 1886 ± 13 Ma, and 1870 ± 18 Ma. On the other hand, the 40Ar/39Ar analyses of the biotite crystals from the Acasta gneiss show a variety of ages. Three samples show the plateau ages of 1877 ± 8 Ma, 1935 ± 14 Ma, and 1951 ± 11 Ma. These plateau ages are a little older than the total gas ages. The 40Ar/39Ar analyses of the amphibole crystals show more varied age rela-tions. The two samples show consistent age relations between the plateau ages (1814 ± 22 Ma and 1964 ± 12 Ma) and the total gas ages (1789 ± 23 Ma and 1967 ± 11 Ma), respectively. Some sam-ples have the apparent old age of 2000 Ma in the middle temperature fractions. These old frac-tions are due to that the originally existed amphibole crystals formed in Archean were affected by the thermal events during the Wopmay orogeny. but did not fully reset. The results suggest that the K-Ar system ages of the biotite and amphibole of the Archean Acasta gneiss that is aged from 4200 to 2600 Ma of zircon U-Pb ages were rejuvenated in the Paleo–Proterozoic ages. The heat source that rejuvenated the K-Ar system ages may have arisen due to the asthenospheric intrusion into the wedge mantle, which took place because of the subduction rollback.

The Vaal Dam catchment, which is the source of potable water for Gauteng province, holds various human activities including mining, urbanization, agricultural and industrial activities coupled with high fluxes of nutrients from different areas within the catchment. This situation led to an enhancement of Harmful Algal Blooms (HABs) in the dam reservoir. Phosphorus and Nitrogen are the limiting nutrients for HABs in many eutrophic aquatic systems when their concentrations are raised in such waters. In this study, multi-time-series plot types and scutter plots were analysed to reveal the relationship between HABs proxy chlorophyll-a (Chl-a) and the potential nutrients. Also (Chl-a) data extracted from landsat-8 satellite images were visualised to show the spatial distribution of HABs in the reservoir. The results showed that the Vaal Dam HABs productivity is a function of the total phosphorus (TP) and the organic nitrogen (KJEL_N) levels, which were positively correlated with chlorophyll-a (Chl-a) concentration. The long-term analysis of Chl-a in-situ data (1986 – 2022) measured at one point within the reservoir showed an average of 11.25μg/l but at some stochastic dates, the Chl-a concentration jumped to very high values reaching the maximum value of 452.8μg/l. Such high values are associated with high records of TP and KJEL_N concentrations at the same dates which clearly reveals their effect on the productivity levels. The decadal time series and its trend analysis showed that the average productivity level of Chl-a increased during the studded period from 4.75μg/l in the first decade (1990 – 2000) to 10.51μg/l in the second decade (2000 – 2010) reaching 16.7 during the last decade (2010 – 2020). The increasing averages of the decadal values are associated with the increasing decadal average of its driving factors, TP from 0.1043 to 0.1096 to 0.1119mg/l for the three decades, respectively and KJEL_N from 0.80mg/l in the first decade to 1.14mg/l in the last decade. The decadal average of temperature showed no significant increase, 17.9 °C in the first decade and 18 °C in the last decade which suggests that temperature is not the only enhancing factor of the HABs productivity in the Vaal Dam. The satellite data analysis during the last decade revealed that the HABs spatial dynamics is a function of the dam geometry and the levels of the discharges from its two feeding rivers. Higher concentrations were observed where the reservoir is meandering and within the areas of restricted water circulation.

Soil salinity is seen as a major restriction for crop production, and with water scarcity this problem becomes more complicated. Mulching is crucial to salinity dynamics management by decreasing evaporation with improving the soil’s characteristics. Using chitosan as an eco-friendly biostimulant can enhance plant defense genes during different abiotic stresses. Recently, agricultural research has recognized nanoparticles as a pioneer material due to their distinctive physicochemical features. Therefore, a lysimeter experiment was conducted to investigate the interactive effects of mulching (UNM: un-mulched, WPM: white plastic, RSM: rice straw and SDM: sawdust) and chitosan foliar application (Ch0: control, Ch1: 250 mg chitosan L-1, Ch2: 125 mg nano chitosan L-1, and Ch3: 62.5 mg nano chitosan L-1) on the biochemical soil characteristics and common beans productivity under salt affected soil conditions. Organic mulching (RSM and SDM) treatments significantly improved the soil's organic carbon, available nutrient content, and total count of bacteria. WPM treatment lowered soil EC to 6.63 dS m-1 and increased soil water content to 34.13%. The application of Ch3 caused considerable increases in the plant height, shoot dry weight, root dry weight, grain yield, and nutrient content in the seed. The total fungi count in the soil and Na% in the seed was significantly decreased due to chitosan foliar applications. Moreover, the interactive effect of different mulch materials plus foliar by chitosan applications gave a statistically similar seed yield in both seasons. Overall, this study revealed the potential of the mulching treatments and foliar application of nano chitosan in improved biochemical soil characteristics and common bean productivity under saline soil conditions.

As the worldwide demand for meat per person is continuously increasing, there is a corresponding rise in the number of livestock animals, leading to an increase in livestock manure. Selecting appropriate treatment technologies for livestock manures is still a complex task and considerable debates over this issue persist. To develop a more comprehensive understanding of the manure treatment framework, this review was undertaken to assess the most utilized manure management technologies and underscore their respective challenges. Anaerobic digestion has become a commercial reality for treating livestock manures. However, the mono-digestion of single substrates comes with certain drawbacks associated with manure characteristics. Anaerobic co-digestion, involving the utilization of multiple feedstocks, holds the potential to overcome these limitations. Extensive research and development have underscored numerous intrinsic benefits co-digestion. These include improved digestibility resulting from synergistic effects of co-substrates and enhanced process stability. This review underscores the limitations associated with the mono-digestion of livestock manures and critically evaluates the advantages of their co-digestion with carbon-rich substrates. Additionally, this review delves into key livestock manure management practices globally, emphasizing the significance of co-digesting livestock manures while addressing the progress and challenges in this field.

Stormwater management is especially critical for urbanized landscapes that border surface waters and therefore must be monitored accurately to meet permitting requirements and mitigate environmental impact. To assess the impact of stormwater pollutants from the university grounds of a large midwestern campus, we pursued the following two objectives. First, to empirically quantify the concentration of four pollutants in campus stormwater (total suspended solids (TSS), total phosphorus (TP), total Kjeldahl nitrogen (TKN), and chlorides (Cl-)) and compare these observations to international averages and modeled values from the Source Loading and Management Model for Windows (WinSLAMM v10.5.0), used by the university for stormwater monitoring. And second, we sought to quantify the steady state infiltration rate of two porous pavements (concrete and asphalt), and two concrete porous paver surfaces (with interlocking aggregates and without) constructed by the university to mitigate environmental impact. Results showed low TSS concentrations relative to other municipalities and modeled results. The discrepancy between modeled and empirical values is argued to arise from spatial and temporal constraints of sampling. Conversely, concentrations of TP, TKN, and Cl-, were at similar levels to reference areas and WinSLAMM, with TP and TKN likely sourced from mainly organic, non-particulate sources (e.g. leaf litter). Of the four mitigation systems, the porous pavers with aggregates had the highest infiltration rate compared to the other three porous pavements, although compounding factors such as age and landcover may have influenced performance differences.

This article systematically reviews the research achievements on the MnOx/TiO2 catalyst doped with transition metals or rare earth metals for the catalytic selective catalytic reduction of NH3 (SCR-NH3) reaction. The Methodi Ordinatio systematic literature analysis method was employed to rank relevant articles based on journal impact factors, publication years, and citation counts. The ranking data shows that the undoped MnOx/TiO2 catalysts exhibit a catalytic efficiency of up to approximately 90% for NOx reduction, while the doped MnOx/TiO2 catalysts with transition metals or rare earth metals can achieve a maximum reduction efficiency of 100%. Among all the doped metals, the catalyst doped with nickel demonstrates the best NOx reduction performance. The comprehensive literature research concludes that MnOx/TiO2-based SCR catalysts, especially those doped with transition metals or rare earth metals, have significant catalytic efficiency and development potential in reducing NOx emissions in SCR reactions.

One of the main challenges in geodetic deformation analysis is to infer whether the geometry of some engineering structures or zones of natural hazards has changed from their initial state or not. The pillar that supports such an analysis is tightly based on the fundamentals of statistical hypothesis testing. The null hypothesis model indicates that no displacement has occurred. It is tested against a class of alternative models, which stipulate different displacement patterns. In this contribution, we present an innovative geodetic displacement detection which integrates combinatorial analysis and likelihood ratio tests into a sequential procedure for the case where the differences between observations of two epochs are in play. This framework is applied and investigated to two test scenarios: a synthetic and a real simulated trilateration network. From a statistical point of view, our approach is rigorous, because the alternative model can identify simultaneously more than one unstable point. In addition, the relationship between the unknown parameters and the observations is always linear, even if the problem manifests itself as non-linear. Consequently, we avoid a potential loss of statistical test power due to the model linearization. In addition, the proposed method controls the false positive rate efficiently. One of the problems that arise here is also related to the selection of the maximum number of points to be considered in the test procedure ( ). Here, we provide an innovative methodology based on rank computation of the design matrices to define , which can even be extended to the problem of outlier detection. Determining avoids the problem of having non-separable models in identifying unstable points. The algorithms and data are available in the repository.

We report on the occurrence of natural Magnesium Alumina Silicate Hydrate (M-(A)-S-H) cement at Feragen and Leka in eastern and western Trøndelag Norway, respectively. Both occurrences are located in the sub-arctic climate zone and form in glacial till and moraine material deposited on ultramafic rock during the Weichselian glaciation. Weathering of serpentinized peridotite dissolve brucite and result in a relative high pH alkaline fluid that subsequently reacts with the felsic minerals of the till (quartz, plagioclase, K-feldspar) to form a cement consisting of an amorphous material or a mixture of nanocrystalline Mg-rich phyllosilicates, including illite. The presence of plagioclase in the till results in the enrichment of alumina in the cement, i.e., forms M-A-S-H instead of the M-S-H cement. Dissolution of quartz results in numerous etch-pits and negative quartz crystals filled with M-A-S-H cement. Where the quartz dissolution is faster that the cement precipitation, a honeycomb-like texture is formed. Compositionally the cemented till (tillite) contains more MgO and has a higher loss of ignition than the till, suggesting that the cement is formed by a MgO fluid that previously reacted with the peridotite. The M-(A)-S-H cemented till represent a new type of duricrust, coined magsilcrete. The study of natural Mg-cement provides information on peridotites as a Mg-source for Mg-cement and as a feedstock for CO2 sequestration.

Carbon monoxide (CO) concentrations in wildfire plumes are easily measured from satellites. This gas can be used as a proxy for carbon dioxide. Forest fires play an important role in the carbon balance and in particular the CO balance. The most likely causes of mega-fires of 2003, 2012, 2021, and 2023 in the Northern hemisphere are heat waves and severe droughts associated with changes in general circulation. Here we analyze satellite data obtained by two different sounders, AIRS and TROPOMI. Different sensitivity to the lowest troposphere allows obtaining information about anthropogenic or pyrogenic contamination of the boundary layer. Shapes of areas polluted by mega-fires in 2019-2020 (Southeastern Australia) and 2021 (Central Siberia) coincide with the areas occupied by coal deposits. The Siberian Lena and Tunguska coal basins are the two largest coal fields in the world. In 2021, their combined area accounted for 90% of fire CO emission from the entire Russian Federation. So strong fires have not observed in this area before. Under- and sub-ground coal combustion may be included into the list of wildfire fuels, at least their role for ignition should be admitted. Further research is needed to assess the importance of coal fires to global climate.

Chlorophyll a concentration (Chl) is a key variable to estimate primary production (PP) through ocean color remote sensing (OCRS). Accurate Chl estimate is crucial for better understanding of spatio-temporal trends of PP over recent decades as a consequence of climate change. However, a number of studies have reported that currently operational chlorophyll a algorithms perform poorly in the Arctic Ocean (AO), which is mainly caused by the interference of colored and detrital material (CDM) with the phytoplankton signal in the visible part of the spectrum. To determine how and to what extent that CDM would bias the estimation of Chl, we evaluated the performances of 8 currently available ocean color algorithms: OC4v6, OC3Mv6, OC3V, OC4L, OC4P, AO.emp, GSM01 and AO.GSM. Our results suggest that the empirical AO.emp algorithm performs the best overall, but for waters with high CDM (acdm(443) > 0.067 m-1), which is of much interest in the Arctic, it is the two semi-analytical GSM models that show better performance. Besides, sensitivity analyses using an Arctic spectrally- and vertically-resolved primary production model further show that errors in Chl mostly propagate proportionally to PP estimates with 7% amplification at maximum. We aslo demonstrate that the higher level of CDM relative to Chl in the water column, the larger the bias would occur in both Chl and PP estimates. Although the AO.GSM overall best performs among algorithms tested in the present study, it tends to fail for a significant number of pixels (16.2% observed in the present study) particularly for waters with high CDM. Our results suggest that an algorithm that provides reasonable Chl estimates for a wide range of optically-complex Arctic waters is still required.

Interdisciplinary STEM and STEAM education give us an opportunity for creativity and educational innovation in a world scenario that needs training in which students can achieve all educational objectives and are prepared to achieve sustainable development. The rural environment with its land is a scenario that provides us with a range of educational resources for the development of STEM and STEAM projects in which students who are better trained and prepared for the needs of today's world are developed, as well as students who are more linked and sensitized to the environment, with the rural environment and its land, so important in our time.  In this article, we will collect examples from Latin America; STEM projects are being developed in which young people establish links with their environment, territory, and the local environment surrounding them. We must look carefully at projects and works in which students' ties with their land and environment are valued through the STEM and STEAM education necessary today. In this scenario, a comparison has been made between Latin American countries and Spain.

We analyzed mineralogical characteristics, and major as well as rare earth element concentrations from a cryptotephra layer in sediments of the infilled maar of Auel (Eifel, Germany). The results of detailed geochemical analyses of clinopyroxenes and their glassy rim of the specific layer are most similar to those from the Campanian Ignimbrite (CI) Tephra occurrence in a loess section at Urluia (Romania). Both records show idiomorphic green clinopyroxenes and formation of twisted minerals up to millimeter scale. The cryptotephra in the Auel core has an age of around 39,940 yr b2k in the ELSA-20 chronology, almost identical to the latest Ar/Ar dates for the Campanian Ignimbrite/Y5 eruption. These observations suggest that parts of the CI ash cloud were transported also northwestward into Central Europe, whereas the main branch of the CI ash plume was transported from southern Italy towards the NE, E and SE.

Colluvial soils play a vital role in the soil composition of western Anatolia, Turkiye, originating from the accumulation of eroded materials at the base of slopes and in closed depressions. It is claimed that colluvial lands are generally unsuitable for agriculture due to slope, shallow soil and nutritional deficiency. However, due to increasing population pressure, agriculture in colluvial lands, which are considered marginal, becomes a necessity as normal agricultural areas are limited in agricultural production. The research hypothesis posits that despite the slope, shallowness of the soil and nutritional deficiency of colluvial lands, if the appropriate plant is selected and the climate and geographical conditions are optimum, strategically important agriculture can be carried out. This study aims to characterize the soil properties of colluvial in western Anatolia, specifically focusing on their agricultural potential for olive, fig, and grape cultivation. Geological origins and topographic features of colluvial were initially assessed, followed by the collection of soil samples from both natural and agricultural areas. Comprehensive analyses were conducted on both colluvial materials and the corresponding soil samples. The findings were statistically evaluated using principal component analysis, with a subsequent discussion on the agricultural sustainability of the soils for the selected plants. The results indicate that the colluvial lands in the study area are generally unsuitable for agriculture due to factors such as slope, erosion risk, shallow soil depth, low soil organic matter, and limited nutritional capacity. However, under favorable climatic conditions, certain specialty crops, such as olives and figs, can thrive, offering economic benefits to the local population. Despite the overall limitations for traditional agriculture, the cultivation of these specific plants contributes to both the economic well-being of the region and the overall sustainability of agriculture in the area.

The effect of climate change plays a significant role on groundwater level variations and crop yield. The change in climate leading to increased temperatures, decreased rainfalls and extreme drought conditions ultimately cause low groundwater level and crop yield. Judicious groundwater management technology viz., water recharge options, need based irrigation, crop selection, must be adapted for further increasing the water table level in soil ecosystem. Additionally, climate change impacts combined with changes in agricultural water use can affect groundwater dynamics. Increased irrigation demand and decreased summer precipitation can lower groundwater levels, impacting crop production. Overall, climate change affects both groundwater resources and crop yield highlighting the need for sustainable water management practices and consideration of soil properties in agricultural modelling. The authors carefully selected relevant research articles addressing the impact of climate change on ground water level in Asian countries. The review highlights the use of machine learning method to ground water level and crop yield modelling. According to the study, machine learning techniques have made significant contributions to predicting groundwater level changes and crop yield with higher accuracies, high performance and less running time.

The removal of harmful arsenic(V) from aqueous solutions using Cyanex 923 (solvation extractant) was investigated under various experimental variables: equilibration time, acidity of the aqueous phase, temperature, extractant and arsenic concentrations, and O/A ratio. Cyanex 923 extracted As(V) (and sulphuric acid) from acidic solutions, thus, its use to remove the metal from slightly acid or neutral solutions it is not possible. Extraction of arsenic is exothermic, and responded to the formation of H3AsO4·nL species in the organic phase (L represented the extractant and the stoichiometric factor n: 1 or 2, depends on the acidity of the aqueous phase). Extraction isotherms are derived from experimental results. Both arsenic and sulphuric acid loaded onto the organic phase can be stripped with water, and stripping isotherms are also derived from the experimental results. The selectivity of the system against the presence of other metals (Cu(II), Ni(II), Bi(III), Sb(III)) are investigated, and also it is investigated the ability of Cyanex 923 to extract As(V) and sulphuric acid against the use of other P=O based solvation reagents, such dibutyl butylphosphonate (DBBP) and tri-butyl phosphate (TBP).

Space and water heating for residential and commercial buildings amount to a third of the European Union’s total final energy consumption. Approximately 75% of the primary energy is still produced by burning fossil fuels, leading to high greenhouse gas emissions in the heating sector. Therefore, policymakers increasingly strive to trigger investments in sustainable and low-emission heating systems. This study forms part of the “Roll-out of Deep Geothermal Energy in North-West-Europe”-project and aims at quantifying the spatial heat demand distribution in the Interreg North-West-Europe region. An open-source geographic information system and selected Python packages for advanced geospatial processing, analysis, and visualization are utilized to constrain the maps. These were combined, streamlined, and optimized within the open-source Python package PyHeatDemand. Based on national and regional heat demand input data, three maps are developed to better constrain heat demand at a high spatial resolution of 100*100m2 for the residential and commercial sectors, and for both together (in total). The developed methodology cannot only be applied to transnational heat demand mapping but also on various scales ranging from city district level to states and countries. In addition, the workflow is highly flexible working with raster data, vector data, and tabular data. Results reveal a total heat demand of the Interreg North-West-Europe region of about 1,700TWh. The spatial distribution of the heat demand follows specific patterns, where heat demand peaks are usually in metropolitan regions like for the city of Paris (1,400MWh/ha), the city of Brussels (1,300MWh/ha), the London metropolitan area (520 MWh/ha), and the Rhine-Ruhr region (500 MWh/ha). The developed maps are compared with two international projects, Hotmaps and Heat Roadmap Europe’s Pan European Thermal Atlas. The average total heat demand difference from values obtained in this study to Hotmaps and Heat Roadmap Europe is 24 MWh/ha and 84 MWh/ha, respectively. It is assumed that the implementation of real consumption data is an improvement in spatial predictability. The heat demand maps are therefore predestined to provide a conceptual first overview for decision-makers and market investors. The developed methods will further allow for anticipated mandatory municipal heat demand analyses.

The Sidi Bou Othmane (SBO) pegmatite district is in the Central Jebilet massif, Occidental Meseta domain, Morocco. The SBO district is hosted essentially in a volcano-sedimentary series composed of the Late-Devonian Sarhlef shales. Pegmatite bodies crop out as dykes, which are oriented from N-S to E-W and are generally variably deformed with ductile and/or brittle structures with ante, syn- or post kinematic criteria. Petrographic observations of pegmatite dykes show that feldspars (i.e., albite, microcline) are the most abundant mineral phases, followed by quartz, micas, with tourmaline and accessory mineral as garnet, and zircon and secondary minerals as clinochlore, sericite, and illite. The geochemical study indicates that, according to the major pegmatite elements dykes of SBO have mainly a S-type granitic composition and are peraluminous granite with calc-alkalic affinity. The study of trace elements pointed out that SBO pegmatite formed under post-orogenic syn-collision context during the Variscan orogeny, by the partial melting of argilliferous sediment and can be ascribed to the muscovite-bearing pegmatite; moreover, they have a good potential on ceramic and contain minerals, such as feldspar, recently assessed as Critical raw materials by European Union.

The important topic of climate change is discussed in this article, with a focus on the historical background and present effects. It draws attention to the differences between climate change and global warming and attributes the faster pace of climate change to human activity, specifically the release of greenhouse gases into the atmosphere. Agricultural practices, deforestation, and the combustion of fossil fuels are examined in conjunction with natural contributors like volcanic emissions. There is discussion of the far-reaching effects of climate change, such as increased temperatures, rising sea levels, harsh weather, and effects on water supplies. The article emphasizes how crucial it is to mitigate and adapt to the effects of climate change by putting in place climate-resilient infrastructure, switching to renewable energy sources, and lowering greenhouse gas emissions. While recognizing the difficulties involved, it examines several approaches, including nuclear energy, wind power, carbon capture and storage, and green building techniques. To successfully address the global challenge of climate change, the conclusion emphasizes the urgent need for joint efforts by scientists, environmentalists, communities, and governments.

Sediment cores were collected from a mudflow lobe (80 m water depth) offshore of the Mississippi River’s Southwest Pass in 2017 to better understand the sedimentology near the lobe entraining the SS Virginia shipwreck (sunk by a German U-Boat in 1942) and surrounding Mississippi River Delta Front. Core analyses included 210Pb/137Cs geochronology, granulometry, and X-radiography. Sediment accumulation rates (SAR) calculated from excess 210Pb activity in multicores are 0.22–0.29 cm/yr at seabed depths less than 20 cm and 0.29–0.51 cm/year at depths greater than 20 cm. 137Cs accumulation rates are ~0.15 to ~ 0.37 cm/year since 1954 and 1963 respectively. Sediment accumulation rates from 210Pb and 137Cs geochronology and indicators of relative sedimentation and bioturbation from X-radiographs suggest that rates of sediment accumulation near Virginia have declined since ca. the mid-20th century. This may be explained by the multi-decade downslope mass transport of the mudflow lobe in which the shipwreck is embedded, and decreases in sediment supply delivered offshore from the Mississippi River. Mass-transport calculations of the Virginia lobe derived from core properties and published lobe advection rates suggest downslope mass transport is far higher than sediment resupply from the Mississippi River, consistent with recent studies of delta retreat.

Based on the theory that certain geological fault zones surpass the influence of other abiotic and biotic site factors for mound-building red wood ants (Formica rufa group), an area northwest of Tuttlingen with extremely high ant density was systematically surveyed, taking into account official geological maps. Indicators of active fault zones were recorded. These were additionally examined in a model area using a high-resolution digital terrain model (DTM 1-meter). The study area is located in the Swabian Jura at the western edge of the Albstadt shear zone, where recent seismic activity is documented by frequent earthquakes. The earthquakes are considered to be the cause of gas permeability in the strike-slip faults, around which the clustered nesting sites were mapped. More than 2900 nests of the Formica rufa group were mapped and their site conditions analysed in different geomorphological positions. In addition to recording forestry site conditions, a geological classification was carried out, as well as an analysis of soil gases/mofettes in areas with the highest nest densities. The correlation between forestry data and nest sites did not reveal a consistent pattern. In contrast, the relationships with gas-permeable strike-slip faults, though predominantly covered with Quaternary sediments, could be identified through CO₂- and CH₄-rich gas emissions, mofettes, and doline features. The interpretations were complicated due to different mapping ages and signatures of the geological maps. Fortunately, this issue could be analysed and evaluated in a sub-area with mappings from 1936/71 and 1995 regarding presumed or confirmed fault trajectories. New insights were gained regarding the relationships between Formica nest sites, gas-permeable faults, and groundwater levels on narrow mountain ridges with steep relief. Here, the lateral emission of CO₂ depends on the groundwater level and does not occur vertically directly above the fault. C- and H-isotope data of CO₂ and CH₄ do not show a consistent source. While methane is mainly derived from biological production by Archaea in the upper crust and in swamp areas, CO₂ mostly originates from the mantle. The results of the investigations revealed that a multitude of geological and ecological factors must be considered for the interpretation of the occurrences of Formica sites northwest of Tuttlingen. These factors confer a distinct originality to this region, contributing not only to an enhanced understanding of site conditions but also furnishing information regarding environmentally relevant gas emissions.

Due to urban sprawls, the arable land is shifting in the settlement areas and towns, while industrial development is making it more vulnerable. The current study was conducted to see the changes in land use and land cover in Kotri area, Pakistan from 1998 to 2020 to establish trends in recent land use development based on available land use data. In this regard, satellite images in the study area were acquired from USGS and processed using ArcMap 10.5 and Environmental for Visualizing Images (ENVI). Results show that; there was a change in the settlement pattern of Kotri city with 40% between 1998 and 2020, 77% decrease in Bare-land was observed in 2020. Natural vegetation in the study area has decreased significantly with 4.4 Sq/ km in 2020, surface water-bodies in 1998 were 1.3 sq/km and in 2020 there is 1.8 Sq/km indicating 32% increase in surface water bodies. It was further revealed that settlement in Kotri has increased due to its geographical location, nearness of the major city of Hyderabad, and the establishment of the industrial zone and educational city near Kotri. From the foregoing, the study concluded that Kotri City will have more changes in its land use and land cover as the expansion in the city is going on and on. It is therefore recommended that local government and provincial government should pay attention towards this development and put up an action plan towards proper provision for such expansion.

Although the statistical methods of downscaling climate data have progressed significantly, the development of high-resolution precipitation products continues to be a challenge. This is especially true when interest centres on downscaling value over several study sites. In this paper , we report a new downscaling method termed the multi-site Climate Generative Adversarial Network (MSCliGAN), which can simulate annual maximum precipitation to the regional scale during the 1950-2010 period in different cities in Canada by using different AOGCM's from the Coupled Model Inter-Comparison Project 6 (CMIP6) as input. Auxiliary information provided to the downscaling model included topography and land-cover. The downscaling framework uses a convolution encoder-decoder U-net network to create a generative network and a convolution encoder network to create a critic network. An adversarial training strategy is used to train the model. The critic/discriminator used Wasserstein distance as a loss measure and on the other hand the generator is optimized using a summation of content loss on Nash-Shutcliff Model Efficiency (NS), structural loss on structural similarity index (SSIM), and adversarial loss Wasserstein distance. Downscaling results show that downscaling AOGCMs by incorporating topography and land-use/land-cover can produce spatially coherent fields close to observation over multiple-sites. We believe the model has sufficient downscaling potential in data sparse regions where climate change information is often urgently needed.

In Summer 2017, huge wildfires in the British Columbia region (Canada) led to the injection of a remarkably high concentration of biomass burning aerosol in the atmosphere. These aerosol masses reached the city of Naples, Italy, since the end of August 2017, where they were characterized by means of a multiwavelength lidar and a sun-sky-lunar photometer. Here we report on the optical and microphysical properties of this aerosol in an intriguing condition, occurring on 4th September 2017, which is characterized by an interesting multi-layered vertical distribution of the aerosol. The Lidar profiles highlighted the presence of four aerosol layers, with two located in the lower troposphere and other two at stratospheric altitudes. A rather thorough characterization of the biomass burning aerosol was carried out. The aerosol depolarization ratio showed an increasing dependence on the altitude with averaged values of 2-4% for the tropospheric layers, which are indicative of almost spherical smoke particles, and larger values in the stratospheric layers, suggestive of aspheric particles. Lidar-derived size distributions were retrieved for the first three aerosol layers, highlighting a higher particle concentration in the fine mode fraction for the layers observed at higher altitude. A dominance of fine particles in the atmosphere (Fine Mode Fraction > 0.8) with low absorption properties (absorption AOD < 0.0025 and SSA > 0.97) was also observed over the whole atmospheric column by sun-photometer data. The space-resolved results provided by the lidar data are consistent with the columnar features retrieved by the AERONET sun-photometer, thus evidencing the reliability and capability of lidar characterization of atmospheric aerosol in a very interesting condition of multiple aerosol layers originating from Canadian fires overpassing the observation station.

The protection of first responders from radioactive contamination of alpha emitters that may result from a radiological accident is of great complexity due to the short range of the alpha particle in air of a few cm. To overcome this issue, for the first time a system for near real-time measuring alpha particles remotely mounted on a UAS has been developed, tested and calibrated. The new system, based on an optical system adapted to be installed on the UAS in order to measure the UV-C fluorescent emitting by the alpha particle in air, has been tested and calibrated carried out by laboratory and in field experiments using UV-C leds and ²⁴¹Am sources. In experimental flights, the probability of detecting a point source was determined to be approximately 60%. In case of a surface extended source, a detection efficiency per unit surface activity of ten counts per second per MBq cm^-2 are calculated. A background count rate of UV-C around 26 ± 28 s^-1 for an integration time of 0.1 s was measured during flights, which leads to a decision threshold surface activity of 5 MBq cm^-2.

Qinghai spruce (Picea crassifolia) is a ecologically important species in the forest ecosystem of the Qilian Mountains region in China. Natural regeneration of this species is critical to maintaining forest ecosystem function. We here analyzed several biological indicators among naturally re-generating Qinghai spruce across several elevations in the Pailugou watershed. Specifically, seedling density, basal diameter (BD), and plant height were measured, as were soil physico-chemical parameters, at 2700 m, 3000 m, and 3300 m above sea level. Differences in the biological indicators and correlations between the indicators and soil parameters were then assessed at each elevation. The results showed that soil stoichiometry was more sensitive to changes in el-evation than seedling indicators were. Furthermore, seedling density was positively correlated with soil pH, whereas BD was positively correlated with the carbon to nitrogen ratio (C/N), the carbon to phosphorus ratio, and soil organic carbon (SOC) contents. None of the analyzed soil parameters had a significant impact on elevation-specific differences in seedling density. However, soil pH, SOC, and C/N significantly affected variations in seedling diameter at each elevation. Finally, soil pH, SOC, C/N, and the carbon to phosphorus ratio significantly affected variations in seed-ling height at each elevation. This study provides a strong theoretical basis for further under-standing of the mechanisms associated with Qinghai spruce regeneration, ulti-mately contrib-uting to rational protection and management strategies for this important natural resource.

Knowledge about the genesis and evolution of black soils in the Eastern Mediterranean is vital for sustainable land management. In this study, the black soils that currently occur in the Eastern Mediterranean were analyzed in different bioclimatic zones and were found to genetically be long to three soil types: 1-Calcareous black soils (Rendzina, Para-Rendzina) (Rendzic or Somerirendzic Leptosols -Typic Rendolls or Lithic Rendolls), 2-Hydromorphic black soils (Calcic Chernozems -Haploxerolls). 3- Black soils on Basalt (Somerirendzic Leptosols) (Haploxerolls). The impact of the relief was obvious on both the thickness of the solum and the mollic horizon. Rendzina occurs on the toe and feet slope, Para-Rendzina on the shoulders, and Chernozems on a flat plain. The color of the epipedon in Rendzina reflects the origin of the prevailing parent material from which they are derived: Proper Rendzina found on limestone, chalk, sandstone, conglomerate, and claystone; Reddish Rendzina on Dolomite and hard limestone, and Grayish Rendzina on Serpentine. It was also found that the Hydromorphic black soils only occur on calcic marl and lacustrine deposits in the depressions arising from the Dead Sea faults under saturation or bad drainage conditions. This soil has a thick, dark mollic horizon and high organic matter content.

Microplastic contamination, defined as plastic particles less than 5 mm in size, has become a major global environmental concern. This study synthesizes findings from carefully chosen studies undertaken in a variety of geographical areas and ecosystems, offering light on the multifaceted issues posed by microplastic pollution. These articles show the global prevalence of microplastics in both land and marine ecosystems. Seasonal fluctuations in microplastic abundance highlight the cyclical nature of this pollution, with larger amounts being reported during the summer months. Tourism, industrialization, and urbanization have all been highlighted as significant contributors to microplastic contamination, stressing the impact of man-made influences. Wastewater treatment plants (WWTPs) have been identified as hotspots for microplastic release into aquatic habitats, emphasizing the need for enhanced treatment procedures. Because microplastics can build up in the food chain, it underlines the possible health problems connected with microplastic pollution for both aquatic creatures and human consumers. Longitudinal studies, geographical variety, in-depth health and ecological impact evaluations, standardization, and effective mitigation methods should be prioritized in future studies. To address this worldwide issue, interdisciplinary collaboration among scientists, health professionals, politicians, and industrial stakeholders is required.

Space exploration presents vast prospects for scientific, industrial, and economic progress. This paper introduces the MeSat mission as a pioneering approach to Mars exploration. MeSat aims to deepen our understanding of Martian conditions and resources by employing an optimized Earth-to-Mars trajectory, enabling a comprehensive study of the Martian atmosphere and surface. The mission comprises a Cargo Microsatellite hosting three 6U CubeSats and two 3U CubeSats, deployed into four separate Mars orbits forming a constellation. Each CubeSat carries distinct payloads: a THz radiometer for water detection, a high-resolution surface camera, a top-tier spectrometer, and a Fourier Transform Spectrometer (FTS) for wind speed readings. This paper focuses on two pivotal innovations: the development of a 183GHz radiometer payload for detecting water on Mars and a optimal mission design algorithm that analyzes a fuel-efficient low-thrust trajectory from Earth to Mars. Regarding the THz payload for water detection, a subharmonic Schottky diode-based mixer is meticulously designed to efficiently down-convert radio signals. The down-converted signals are carefully analyzed using a customized Do-It-Yourself (DIY) spectrum meter, which facilitated the capture and processing of acquired data. To provide the necessary Local Oscillator signals for the mixer, a Tripler employing three-anode Schottky diodes is developed. Additionally, the Tripler requires a signal generator for its entry frequency, which is addressed by developing a DIY signal generator. Together, these components, comprising the Schottky diode mixer, Tripler, and DIY circuits, collectively form the complete THz payload, demonstrating exceptional power efficiency with a total consumption of only 3.7W. The study employs a dual-step hybrid optimization algorithm (PSO-Homotopy) to analyze fuel-efficient low-thrust trajectories from Earth to Mars, incorporating the Ephemeris dynamics model to account for gravitational perturbations in the entire solar system. In practical mission design, crucial factors like hyperbolic excess velocity, diverse opportunities for Earth launch and Mars rendezvous, varied propulsion systems, and Time of Flight (TOF) play vital roles in trajectory optimization.

The identified Urban Heat Island (UHI) phenomenon, coupled with diminished vegetation and anthropogenic heat release, poses a significant environmental challenge for major urban centers. Particularly worrisome is the UHI effect in hot and temperate climates such as the Mediterranean region during the summer season. This exacerbates discomfort and heightens the risks of diseases linked to high temperatures. Additionally, it contributes to environmental consequences, including elevated electricity consumption due to increased demand for cooling [1]. The utilization of Remotely Sensed imagery for estimating Land Surface Temperature has become more prevalent in various applications associated with evaluating urban micro-climates and the Urban Heat Island (UHI) phenomenon. This study presents an algorithm for the automatic mapping of Land Surface Temperature (LST) from Landsat-8 data using a vegetation index-based technique in the Google Earth Engine (GEE) platform. The primary aim is to discern patterns and trends in LST over a 5-year period, from 2017 to 2021. The application was tested in the urban area of Thessaloniki, Northern Greece, which is particularly representative of the Mediterranean urban environment. Computation of Normalized Difference Indices (NDVI, NDBI, NDWI) for the study area was also performed within the GEE platform and correlation analysis was implemented to evaluate the impact of the urban landscape on the distribution of LST.

Due to urban sprawls, the arable land is shifting in the settlement areas and towns, while industrial development is making it more vulnerable. The current study was conducted to see the changes in land use and land cover in Kotri area, Pakistan from 1998 to 2020 to establish trends in recent land use development based on available land use data. In this regard, satellite images in the study area were acquired from USGS and processed using ArcMap 10.5 and Environmental for Visualizing Images (ENVI). Results show that; there was a change in the settlement pattern of Kotri city with 40% between 1998 and 2020, 77% decrease in Bare-land was observed in 2020. Natural vegetation in the study area has decreased significantly with 4.4 Sq/ km in 2020, surface water-bodies in 1998 were 1.3 sq/km and in 2020 there is 1.8 Sq/km indicating 32% increase in surface water bodies. It was further revealed that settlement in Kotri has increased due to its geographical location, nearness of the major city of Hyderabad, and the establishment of the industrial zone and educational city near Kotri. From the foregoing, the study concluded that Kotri City will have more changes in its land use and land cover as the expansion in the city is going on and on. It is therefore recommended that local government and provincial government should pay attention towards this development and put up an action plan towards proper provision for such expansion.

Organic horticulture is a holistic management system which follows good production practices and should be considered as the cornerstone of mitigating climate change and to produce healthier fruits and vegetables. This agroecosystem practice not only benefits the green economy but promotes and enhances soil biological activity, biodiversity, and other biological cycles in the sphere. The last decade has observed a rise in the production and consumption of organically certified agricultural products due to their higher nutritional value, lowered risk of exposure to harmful chemicals and improved organoleptic properties. The aim of this review was to demonstrate the considerable impact of organic horticulture on mitigating climate change and simultaneously satisfy consumer needs. The outcome of this review demonstrates that there are still numerous research studies required to evaluate how different farming systems and pedoclimatic conditions can contribute to more efficient horticultural practices.

Carbon offsetting is currently a major tool in managing carbon emissions and the drive to Net-Zero. This study aims to identify the offsetting potential of existing conservation schemes, and whether carbon offsetting credits could potentially finance the continued management of the conservation activities. The results from Dorset, in the UK indicate that many existing conservation schemes in woodland, heathland and grasslands can not only enhance biodiversity but also capture significant amounts of carbon. We show that the cost per additional tonne of carbon sequestered as a result of conservation activities varies considerably between different conservation projects. On average, the cost of this offsetting is £80 per tonne CO2e sequestered and ranging between £120 and £0 depending on the project and whether existing biodiversity grants would be available. However, this figure was based on adapting and refining existing conservation projects, and did not involve expensive factors such as purchase of land, which make the prices potentially unrealistic. While the costs identified are higher than many offsetting schemes at present, it could present a useful option for those wishing to localise their offsetting, and could be combined with biodiversity credits or other credit schemes to make the higher costs more attractive.

In the last years, new findings and new methods (stable isotopes of oxygen, zinc and nitrogen, 2D and 3D modelling, geometric morphometric analyses of the teeth) have enhanced our knowledge of the Neogene shark fauna and its palaeobiology. Several papers deal with the large Otodus (Megselachus) species, including the construction of a 3D model as well as insights into lifestyle and diet. In addition, skeletal remains of Carcharias gustrowensis, Carcharodon hastalis, Keasius parvus and a natural tooth set of Carcharodon hubbelli have been described in the last 13 years, and the dentition of the Neogene species Carcharoides catticus, Megachasma applegatei and Parotodus benedenii have been reconstructed. Stable isotope analyses of the teeth from the Neogene species of Araloselachus, Carcharias, Carcharodon, Galeocerdo, Hemipristris, and Mitsukurina have given insights into the trophic position of these genera during the Neogene, and shark teeth preserved near skeletal remains of prey animals (mammals) and shark bite traces on these remains provide direct evidence of trophic interactions. Tooth shape, fossil locality and palaeoenvironment have been used to better understand the taxa Carcharhinus dicelmai, Megalolamna paradoxodon, Pachyscyllium dachiardii and P. distans. Among extant species, Galeorhinus galeus can be traced back to the Eocene. The following taxa can be traced back to the Oligocene: ?Alopias superciliosus, and Rhincodon typus. Species already present in the Miocene include: Alopias vulpinus, Carcharhinus amblyrhynchoides, C. amblyrhynchos, C. albimarginatus, C. amboinensis, C. brachyurus, C. brevipinna, C. falciformis, C. glaucus, C. leucas, C. limbatus, C. longimanus, C. macloti, C. obscurus, C. perezi, C. sealei, ?Carcharodon carcharias, Centrophorus granulosus, Cetorhinus maximus, Dalatias licha, Deania calcea, Galeocerdo cuvier, , Glyphis glyphis, Heptranchias perlo, Isurus paucus, Lamna nasus, Negaprion brevirostris, Odontaspis ferox, Pseudocarcharias kamoharai, Sphyrna media, S. mokarran. First appearing in the Pliocene are: Scymnodon ringens, Somniosus rostratus, Zameus squamulosus. For some extant species (Carcharias taurus, Hexanchus griseus, Isurus oxyrinchus, Notorynchus cepedianus, Sphyrna zygaena) it is not clear if the assigned Neogene teeth represent the same species. Applying these new methods to more fossil shark taxa, a detailed search for shark fossils, as well as better knowledge of the dentition of extant species (especially those with minute-sized teeth) will further enhance knowledge of the evolution and palaeobiology of sharks.

The transportation sector stands out as California's primary contributor to greenhouse gas emissions, necessitating urgent action from government agencies to promote the adoption of low-carbon transportation (LCT) within the heavy-duty vehicles (HDV) and off-road equipment (ORE) sectors. This study conducts content analysis to delve into the impact of behavioral factors, specifically awareness and impression, on LCT adoption within these sectors. The analysis results are honed using a generative artificial intelligence (AI) tool. Positive associations emerge between the potential for LCT adoption and awareness, as well as factors linked to LCT (government incentives, environmental considerations). Notably, the study reveals that financial barriers and incentives hold greater significance for small-fleet organizations compared to their large-fleet counterparts. These findings offer actionable insights for government agencies to formulate targeted strategies, including mandates and incentives, tailored to the unique needs of organizations within the HDV and ORE sectors.

Multiple sources influence air quality and regional climate in complicated atmospheric emission situations like urban agglomerations. To resolve pollution plumes and source influences in polluted areas, a comprehensive chemical fingerprinting of sources utilizing non-methane hydrocarbons (NMHCs) and the identification of acceptable tracer molecules and emission ratios is required, in contrast to pristine locations, where reliance on a single or a few chemical tracers is frequently sufficient. We have characterized the prevalence of NMHCs fingerprints in the urban areas and quantified the correlation of windspeed with the concentration of these pollutants. eNose sensors and Air quality management stations provide the data to identify the emission sources of such pollutants. Based on our analysis, the average NMHC concentration in 2021 has been recorded 0.424 ppm at point 1 AQMS whereas at point 2 AQMS it was 0.256 ppm. Such outcomes could be attributed to the proximity of emissions sources, the direction and speed of the wind, or both. Moreover, traffic can be a major contributor to pollution levels in any urban area. More research based on a larger dataset is required before definitive conclusions can be drawn, and viable solutions can be proposed.

Cities are important sources of anthropogenic methane emissions. Municipal governments can play a role in reducing those emissions to support climate change mitigation, but they need information on the rate of emissions to context mitigation actions and track progress. Here, we examine the application of satellite data from the TROPOspheric Monitoring Instrument (TROPOMI) to estimate city-level methane emissions rates in a case study of the City of Calgary, Alberta, Canada. While satellites are touted as a global methane monitoring system, we found limited observational coverage over Calgary that precluded the reliability of measurement-based models to track the annual emissions. In this work, we integrated valid observations over three years (2020-22) and used mass balance modeling to derive a long-term averaged emission estimate. The column-averaged dry-air mole fraction (XCH4) enhancement over Calgary was small, 4.7 ppb, but within the city boundary, we identified local hot spots in the vicinity of known sources (wastewater treatment facility and landfills). The city-scale emissions estimate from mass balance was 215.4 ± 132.8 t/d CH4. This estimate is approximately four- and six-times larger than estimates from Canada's gridded national inventory report of anthropogenic CH4 emissions and the Emissions Database for Global Atmospheric Research (EDGAR v8.0), respectively. Valid observations are more common in warmer months and occur during a narrow daily overpass timeslot over Calgary – these effects may bias the emissions estimate. Overall, the findings from this case study highlight the challenge of deriving routine (sub-annual to annual) satellite-based estimates of city-scale methane emissions in similar geographic settings and suggest that more granular emissions inventories are needed to improve methane reporting.

Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks whose automation was analyzed consisted in estimating changes in the roughness of a mountain streambed and the extent of floods from images. The Segment Anything Model (SAM) developed this year by Meta was used for this purpose. Images from many years from the Wielka Puszcza mountain stream located in the Polish Carpathians were used as the only input data. The model was not additionally trained for the described tasks. The model can be run in several modes, but the two most appropriate were used in this study. The first one is available in the form of a web application, while the second one is available in the form of a Jupyter notebook run in the Google Colab environment. Both methods do not require specialized knowledge and can be used by virtually any hydrologist. In the roughness estimation task, the average Intersection over Union (IoU) ranges from 0.55 for grass to 0.82 for shrubs/trees. Ultimately, it was possible to estimate the roughness coefficient of the mountain streambed between 0.027 and 0.059 based solely on image data. In the task of estimation of the flood extent, when selecting appropriate images, one can expect IoU at the level of at least 0.94, which seems to be an excellent result considering that SAM is a general-purpose segmentation model. It can therefore be concluded that SAM model can be a useful tool for a hydrologist.

Soil moisture reserve is a key factor in maintaining soil fertility and all other related ecosystem services (including carbon sequestration, soil biodiversity, soil erosion control). In semiarid blown-sand areas under aridification water preservation is a particularly crucial task for agriculture. The international Diverfarming project (2017–2022) within the EU Horizon 2020 Program focused on the impacts of crop diversification and low-input practices in all pedoclimatic regions of Europe. In the three-year experiment conducted in the Pannonian region the impacts of intercropping asparagus with different herbs on some provisioning and regulating ecosystem services were evaluated in the Kiskunság sand regions. Relying on the findings based on a range of measured physical and chemical soil parameters and on crop yields and qualitative properties, advice was formulated for farmers. The message drawn from the experiment is somewhat ambiguous. The local farmer agrees that crop diversification improves soil quality, but he denies that it would directly influence farm competitiveness, which primarily depends on cultivation costs (such as fertilization, plant protection and labour). Further analyses are needed to prove the long-term benefits of diversification through enriching soil microbial life and the possible reduction of fertilizer use while water demand is kept at a low level and the same crop quality is ensured.

The past is an important lesson for facing the future with greater awareness. In this context, school plays a key role to spread knowledge on natural phenomena and to promote behavior change. Together with researchers, teachers can be strong allies to build more resilient future citizens. The Istituto Nazionale di Geofisica e Vulcanologia (INGV) school training activities provide tools to get ready for the next earthquake and/or tsunamis. About 5000 students from both Middle schools (ISCED 2) and High schools (ISCED 3) were involved in active learning activities based on a flipped-up approach during special online scientific events in the Pandemic. Online lab activities were conducted respectively during the European Researchers’ Night (“Earthquakes: history teaches us the future: researchers for a day with experimentation in didactics for ESL”) and during the World Water Day 2021 and the World Earth Day 2021 (“Tsunamis: history teaches us the future researchers for a day with experimentation in didactics for ESL”). These two Episodes of Situated Learning (ELS) experiences triggered students’ interest, favoring remote learning, developing life skills, focusing on historical seismic studies of both past earthquakes and tsunamis.

Paddy fields are classified as wetland environments, and they comprise a freshwater ecosystem. They are ecologically important habitats and breeding grounds for many aquatic insects, amphibians, and reptiles. However, the paddy field ecosystem is constantly threatened by climate change and indiscriminate use of pesticides. The meta-barcode analysis of eDNA (environmental DNA) method is highly effective in accumulating information on many organisms that inhabit the paddy field ecosystem because it can explore organisms that are difficult to identify with traditional sampling methods. The eDNA method is very effective for accumulating information on many organisms in the rice field ecosystem. It can indirectly identify the existence of taxa no longer found in the target ecosystem due to behavioral characteristics like amphibia. In the metabarcoding results of this study, genes of more than five species of frogs were found, but it was impossible to confirm all frog taxa, frog's morphological pictures, and croak sounds. On the other hand, some frog taxa had been found only in the metabarcoding analysis. The eDNA of frogs found only in metabarcoding is estimated to have been introduced from nearby areas inhabited by frogs rather than the target region. Due to the powerful analytical resolution of eDNA metabarcoding, this eDNA-based paddy field search is expected to help investigate the biodiversity in agricultural ecosystems.

The geographical location of Yunnan province is at the upstream area of water vapor transportation from the Bay of Bengal and the South China Sea to inland China. Understanding the spatiotemporal variations of water vapor over this region holds significant importance. We utilized the GNSS data collected from 12 stations situated in Yunnan, which are part of Crustal Movement Observation Network of China, to retrieve hourly precipitable water vapor (PWV) from 2011 to 2022. The retrieved PWV at Station KMIN were evaluated by the nearby radiosonde data, and the result shows that the mean bias and RMS of the differences between the two datasets are 0.08 and 1.78 mm respectively. Average PWV values at these stations are in the range of 11.77 to 33.53 mm, which decrease from the southwest to the north of Yunnan and are negatively correlated with the station heights and latitudes. Differences between average PWV in wet season and dry season range from 12 to 27 mm. These differences tend to increase as the average PWV increases. The yearly rates of PWV variations, averaging 0.18 mm/year, are all positive for the stations, indicating a year-by-year increase in water vapor. Amplitudes of the PWV annual cycles are 9.75-20.94 mm. The spatial variation of these amplitudes is similar to that of average PWV over the region. Generally, monthly average PWV values increase from January to July and decrease from July to December, and the growth rate is less than the decline rate. Average diurnal PWV variations show unimodal PWV distributions over the course of the day at the stations except Station YNRL, where bimodal PWV distribution was observed.

The paper aims to introduce user-friendly modelling approaches to analyze how abiotic factors influence various trophic levels within the marine ecosystem, both naturally and through human impact. It specifically investigates the connections between environmental parameters (like temperature, salinity, and nutrients) and plankton along the Romanian Black Sea coast during the warm season (May-September) over a decade. Utilizing machine learning (ML) algorithms and data collected during this period, models were developed to project the proliferation of zooplankton. During the warm season, water temperature emerged as a significant factor affecting copepods and “other groups” zooplankton densities, while no discernible impact was noted on Noctiluca scintillans blooms. Salinity fluctuations notably influenced typical phytoplankton proliferation, with phosphate concentrations primarily driving widespread blooms. Two scenarios were explored for forecasting zooplankton growth: Business as Usual, predicting modest increases in temperature, salinity, and constant nutrient levels, and the Mild scenario, anticipating more substantial temperature and salinity increases while nutrients decrease significantly by 2042. The findings highlight that under both scenarios, Noctiluca scintillans displays notably high densities, with the second scenario projecting even higher values, surpassing the first by around 70%. These densities indicate characteristics of a eutrophic ecosystem, suggesting the potential implications of altered abiotic factors on ecosystem health.

In this study, tree selection/plantation DSS (Decision Support Systems) were reviewed and assessed based on essential objectives in the available literature. We reviewed existing DSS using multiple data sources and available online resources such as web interfaces. We compared the existing DSS, focusing primarily on five primary objectives in this study, which DSS may address when it comes to the tree selection, including a) Climate resilience, b) Infrastructure/Space Optimization, c) Agroforestry, d) Ecosystem services, e) Urban sustainability. Climate resilience of tree species and urban sustainability is addressed relatively less in existing systems, which can be holistically internalized in future DSS tools Based on this review, DNN (Deep Neural Networks) is recommended to address achieving trade-offs between complex objectives such as maximizing ecosystem services, climate resilience of tree species, maintaining Agroforestry, and other benefits.

The Earth's water resources, totaling 1.386 billion cubic kilometers, predominantly consist of saltwater in oceans. Groundwater, plays a pivotal role, with 99% of usable freshwater supporting 1.5–3 billion people as drinking water source and 60–70% for irrigation. Climate change, with temperature increase and altered precipitation patterns, directly impacts groundwater systems, affecting recharge, discharge, and temperature. Hydrological models are crucial for assessing climate change effects on groundwater, aiding in management decisions. Advanced hydrological models, incorporating data assimilation and improved process representation, contribute to understanding complex systems. Recent studies, employ numerical models to assess climate change impacts on groundwater recharge that could help in management of Groundwater. Groundwater vulnerability assessments vary with the spatial and temporal considerations, as well as assumptions in modelling groundwater susceptibility. The review assesses the vulnerability of groundwater to climate change and stresses the importance of accurate assessments for sustainable water resource management. It highlights challenges in assumptions related to soil and aquifer properties, multiple stressors, adaptive capacity, topography, aquifer properties, and groundwater contamination processes and gradual sea level rise scenarios and realistic representations of the region of study. The advancements in hydrological modelling, including the integration of uncertainty quantification and remote sensing data, artificial intelligence, could assist in the efforts to improve models for assessing the impacts of climate change on hydrological.

The two-scale method (TSM) is an effective approach to simulate electromagnetic (EM) scattering from rough sea surface, to interpret physical interaction of EM wave with rough sea surfaces. The sea surface roughness spectrum and the cutoff wavenumber are two key factors affecting the accuracy of TSM simulation. This paper takes the geophysical model functions (GMFs) of different band as reference, and quantitatively studies the two factors based on the numerical simulation of different polarization backscattering coefficients. The numerical simulation demonstrates that Apel spectrum is more suitable for the backscattering simulation in C/X/Ku-band, and the optimal cutoff wavenumbers are also derived for TSM simulation of EM scattering in C/X/Ku-band. Then an empirical model function of optimal cutoff wavenumbers with respect to frequency, incident angle and wind speed are obtained with regression method. Finally, the simulation results with the new model function of cutoff wavenumber are compared with the GMF and measured data in different bands and they are all consistent. Moreover, a physical explanation for the optimal cutoff wavenumber is also given.

The ocean of the planet Earth, which is as thin as a cicada's wings, play a role of catalyst to the evolving of the ancient plates. The ocean and the ancient plates of the planet Earth formed a magic Whirlpool of the Cross “十” shape with double whirl arms. The central core of the Cross “十” shape Ocean-Plate Whirlpool is the Hint Black Hole (HBH) located at the Northwestern Pacific Ocean floor which is decorated with invisible geological age distribution of clam shell. The double whirl arms of ancient plates are distinguished to be left and right at Bering Strait and just formed the ring of fire of the Pacific Ocean.The Cross “十” shape Ocean-Plate Whirlpool of the planet Earth was born at the equatorial area about 66 Ma ago and is rotating anticlockwise and drifting northward by a mini footprint of spiral at s speed of as slow as a snail moves. Obviously, it would come to an end at the North Pole about 100 Ma in the future. So, the lifespan of the Cross “十” shape Ocean-Plate Whirlpool would be about 166 Ma, from birth to death on the planet Earth.What is hidden behind of the evolving of the oceans and the ancient plates is the golden law of geometrical progression of ladder pagoda of attributes evolving of them, which is “1➨2➨4➨2➨1”, including upgrading and downgrading process. It seems to hint that what is happening on the planet Earth, including the top-level species of human race, is actually unique in the Milky Way galaxy in essence.The property roles of expanding and shrinking are existing in the Cross “十” shape Ocean-Plate Whirlpool by face to face and the exchange of property roles took place tens of millions of years ago. And that situation would happen again tens of millions of years in the future. It seems a giant circle of evolving of the exchange of property roles would be drawn by the Cross “十” shape Ocean-Plate Whirlpool in her lifetime.

Olive orchards cover over 10 million hectares worldwide, with production techniques undergoing significant changes in the past three decades. The traditional rainfed approach, involving minimal inputs, has given way to irrigated super-intensive systems with higher planting density, in-creased productivity, greater use of fertilizers and phytopharmaceuticals, and total mechaniza-tion. Its impact on soil chemical properties remains a topic of great debate and no definitive consensus has been reached. Our main objective was to examine the different effects of traditional olive orchards and super-intensive ones on soil chemistry over a decade. We collected and ana-lyzed 1500 soil samples from an irrigation perimeter in southern Portugal in 2003 and 2013. Our findings indicate that compared to traditional olive orchards, super-intensive ones show, in a decade, a significant decrease in soil organic matter (less 22.8% - p<0.001) and an increase in so-dization (more 33.8% of Ext Na - p<0.001) highlighting the importance of monitoring this factor for soil fertility. In comparison to other irrigated crops in the region, super-intensive olive orchards promote a significant soil acidification (from 7.12 to 6.58), whereas the pH values of the other crops increase significantly (more 3.3%, 13.5%, 3.0% in corn, tomato and cereals, respectively). Mainly because organic matter levels decrease, soil acidification and soil sodization we can un-derline that hedgerow olive orchards can affect soil characteristics negatively when compared with traditional ones.

This research review paper comprehensively assesses the environmental impacts of diverse energy sources and proposes sustainable solutions. Fossil fuels contribute to pollution, habitat destruction, and greenhouse gas emissions. Renewable energy offers cleaner alternatives but faces challenges in manufacturing and disposal. Nuclear power has low emissions but poses risks in waste management and radiation. Biomass can be sustainable if responsibly sourced, but unsustainable practices lead to deforestation and emissions. Solutions include renewable technologies, energy efficiency, carbon capture, and sustainable transportation. Effective policies, incentives, and individual actions are crucial for a greener future. This review highlights the urgency of addressing energy-related environmental impacts and offers valuable insights for policymakers and individuals to take decisive actions for a sustainable energy future that protects the environment and promotes well- being.

The Advanced Meteorological Image (AMI) onboard GEOKOMPSAT 2A (GK-2A) enables the retrieval of dust aerosol optical depth (DAOD) from geostationary satellites using infrared (IR) channels. IR observations allow the retrieval of DAOD and the dust layer altitude (24 hour) over surface properties, particularly over deserts. In this study, dust events in northeast Asia from 2020 to 2021 were investigated using five GK-2A thermal IR bands (8.7, 10.5, 11.4, 12.3, and 13.3 μm). For the dust cloud, the observed brightness temperature differences (BTDs) of 10.5 and 12.3 μm were found to be always negative, while the BTD of 8.7 and 10.5 μm varies relying on the dust intensity. Making the best use of optical properties, a physical approach for DAOD lookup tables (LUTs) was developed using IR channels to retrieve the DAOD. This study simulated the characteristics of thermal radiation transfer using the forward model and dust aerosols can explain by BTD (10.5, 12.3 μm), which is an intrinsic characteristic of dust aerosol. The DAOD and property of dust can be gained from the brightness temperature (BT) of 10.5 μm and the BTD of 10.5, 12.3 μm. Additionally, the cumulative distribution function (CDF) was employed to strengthen the continuity of 24-hour DAOD, which was applied to the algorithm by calculating the conversion value coefficient for the DAOD error correction of the IR with daytime visible aerosol optical depth (VAOD) as the true value. The results show that DAOD product can be successfully used during both daytime and nighttime to continuously monitor the flow of yellow dust from the GK-2A satellite in northeast Asia. In particular, the validation result of IR DAOD was similar to that of the active satellite product (CALIPSO/CALIOP), which showed a tendency similar to that for IR DAOD at night.

Remote Sensing and Geographic Information System are recognized as crucial instruments for conducting geographical and geospatial research. RS and GIS technology was employed to assess the morphological Characteristics of the Kasura River Watershed situated within the Parbhani and Jalna Districts of Maharashtra, India. The entire drainage area of the Kasura River basin measures 490.13 square kilometers (km²). Various morphometric characteristic were calculated and examined, encompassing linear features such as stream number, stream order, mean stream length, stream length, and stream length ratio, areal attributes including elongation ratio, circularity ratio, form factor, constant of channel maintenance, drainage density and drainage texture and relief characteristics such as relief, relief ratio, maximum relief, ruggedness number, relative relief, and length of overland flow. These findings underscore the significance of employing morphometric analysis in watershed assessment, offering a quantitative method for characterizing the surface attributes of a drainage pattern and yielding valuable insights into the topography and runoff dynamics of the region.

Keywords: Academic Trends; Energy Consumption; Higher Education Institutions; Systematic Literature Review; Scholarly output; University buildings

Global climate change has induced a rise in sea surface temperature (SST), although this increase is not uniform across the world. Significant variations exist between coastal and offshore waters, particularly in regions affected by upwelling processes. This study focuses on the Canary Current Upwelling System (CCUS), stretching from Northwest Iberia to Northwest Africa. High-resolution remotely sensed SST data (0.05°) from the ODYSSEA Level 4 Sea Surface Temperature Reprocessed dataset were validated with in-situ measurements and employed to establish a regional climatological baseline for 1982 – 2012. Subsequent years were compared to this baseline to construct SST anomaly maps, revealing SST changes since 2012. The study area was further divided into sub-regions for comparative analysis. Results indicate that SST consistently increased at a higher rate offshore compared to the adjacent nearshore regions. A reference dataset spanning 1951 – 1981 was used to gauge SST variability between the two baselines. SST exhibited a 0.59°C increase from 1951 – 1981 to 1982 – 2012, with a slowing of SST trends beyond the 1982 – 2012 baseline. This research offers valuable insights into the climatological dynamics of the CCUS. These findings enhance our understanding of this critical coastal system's climatology, laying the groundwork for future investigations into evolving climate patterns in coastal regions.

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advance in technologies for the use of urban wind energy has turned this source into an attractive alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open-access geographic reference systems tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consult, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found 24 provinces have poor potential, below &lt;4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 - 6.63 m/s. The population density was established and was observed that the provinces with greater potential are less densely populated. Through 59 interviews 28 institutions were identified and evaluated due to their relevance in decision-making for the implementation of energy projects. The MEM has strongly categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

ZnO thin films with a thickness of 300 nm were deposited on Si and Al2O3 substrates using electron beam evaporation technique with the aim to be tested as low cost and low power consumption gas sensors for ozone (O3). To characterize the surface roughness and the grain size, which are the main parameters recognized to enhance gas sensitivity since they directly influence the effective sensing area, surface morphology and roughness analyses of the films were performed using scanning electron microscopy and atomic force microscopy, respectively. The crystalline structure and elemental composition were studied through Raman spectroscopy and X-ray photoelectron spectroscopy. Gas tests were conducted at room temperature and zero-bias voltage to assess the sensitivity and response as a function of time of the films to O3 pollutant. The results indicate that the films deposited on Al2O3 exhibit promising characteristics, such as high sensitivity and a very short response time (< 2 s) to the gas concentration. Additionally, it was observed that the films display pronounced degradation effects after a significant exposure to O3.

Biocides used in antifouling (AF) paints, such as 4,5-dichlorine-2-n-octyl-4-isothiazole-3-one (DCOIT), can gradually leach into the environment. Some AF compounds can persist in the marine environment and cause harmful effects on non-target organisms. Nanoengineered materials, such as mesoporous silica nanocapsules (SiNC) containing AF compounds, have been developed to control their release rate and reduce their toxicity to aquatic organisms. This study aimed to evaluate the acute toxicity of new nanoengineered materials, SiNC-DCOIT and a silver-coated form (SiNC-DCOIT-Ag), as well as the free form of DCOIT and empty nanocapsules (SiNC), on the sun coral Tubastraea coccinea. T. coccinea is an invasive species and can be an alternative test organism for evaluating the risks to native species, as most native corals are currently threatened. The colonies were collected from the Alcatrazes Archipelago, SP, Brazil, and acclimatized to laboratory conditions. They were exposed for 96h to different concentrations of the tested substances: 3.33, 10, 33, and 100 µg L-1 of free DCOIT; 500, 1000, 2000, and 4000 µg L-1 of SiNC; and 74.1, 222.2, 666.7, and 2000 µg L-1 of SiNC-DCOIT and SiNC-DCOIT-Ag. The test chambers consisted of 500 mL flasks containing the test solutions, and the tests were maintained under constant aeration, constant temperature of 23 ± 2°C, and photoperiod of 12h:12h (light/dark). At the end of the experiments, no lethal effect was observed; however, some sublethal effects were noticeable, such as the exposure of the skeleton in most of the concentrations and replicates, except for the controls, and embrittlement at higher concentrations. Adults of T. coccinea were considered little sensitive to the tested substances. This resistance may indicate a greater capacity for proliferation of the species, which is favored in substrates containing antifouling paints, to the detriment of the native species.

This paper is a follow-up to a previous study that was conducted in a research forest and identified the optimal method for Diameter at Breast Height (DBH) estimation as a circular scanning and fitting ellipses to 4cm stem cross-sections at breast height. The aim of this study was to determine whether the identified method is applicable to natural boreal forests as well. The iPad Pro LiDAR scanner was used to acquire point clouds for 15 sites representing a range of natural boreal forest conditions in Ontario, Canada, and estimate DBH. The secondary objective was to determine if tested stand (Species composition, age, density, understory) or tree (Species, DBH) factors affected the accuracy of estimated DBH. Overall, estimated DBH values were within 1cm of actual DBH values for 78 of 133 measured trees (59%). An RMSE of 1.5cm (8.6%) was achieved. Stand age had a large effect (&gt;0.15) on the accuracy of estimated DBH values, while density, understory, and DBH had moderate effects (0.05-0.14). No trend was identified between accuracy and stand age. Accuracy improved as understory density decreased and as tree DBH increased. Inertial Measurement Unit (IMU) and positional accuracy errors with the iPad Pro scanner limit the feasibility of using this device for forest inventories.

Climate-induced changes contribute to the thawing of ice-rich permafrost in the Arctic, which leads to the release of large volumes of organic carbon into the atmosphere in the form of greenhouse gases, mainly carbon dioxide and methane. Ground ice constitutes a considerable volume of the cryogenically sequestered labile dissolved organic carbon (DOC) subjected to fast mineralization upon thawing. In this work we collected an unique geochemical database of the ground and glacier ice comprising the samples from various geographic locations characterized by a variety of key parameters, including ion composition, carbon-bearing gases (methane and carbon dioxide) bulk biogeochemical indicators and fluorescent dissolved organic matter (DOM) fractions. Our results show that interaction with solid material—such as sediments, detritus, and vegetation—is likely the overriding process in enrichment of the ground ice in all the dissolved compounds. Terrigenous humic-like dissolved organic matter was predominant in all the analyzed ice samples except for glacier ice and pure tabular ground ice from Mare Sale (Western Yamal). The labile protein-like DOM, indicating an autochthonous source, showed no correlation to humic components and probably associated with microbial abundance in the ground ice. The sum of the fluorescent DOM components satisfactory correlates to DOC, indicating the adequacy of the estimation. The pure tabular ground ice samples exhibit the highest biogeochemical quality which may be responsible for the amplification of permafrost organic matter decomposition upon thawing. Yamal impure tabular ground ice and ice wedges are extremely enriched in methane compared to the samples from other locations which should cause a portion of direct methane emission upon the putative thawing.

Higher traffic density in Russian cities and less uniform traffic due to congestions are reasons for increased emissions of pollutants contained in exhaust gases of vehicles. The paper presents the modeling results of pollutant dispersion in Magnitogorsk. The analysis of these results shows that now many blocks of flats and social infrastructure of the city are in a zone with an excess of maximum allowable concentration of pollutants. Having summarized the methodological framework formulated by Russian and foreign researchers, the authors systemized the existing methods used to decrease pollutants produced by vehicles. It is proposed to choose an optimal combination of such methods applying a developed mathematical model. By adopting an optimal combination of the methods, it is possible to ensure minimum air pollutant emissions from vehicles, allocating limited financial resources. The mathematical modeling of the solutions on changing traffic density and structure and implementing methods used to decrease pollutants on one of the Magnitogorsk crossroads with the heaviest traffic is used to draw a conclusion about efficiency of the designed model used as a tool for strategic planning of development and transformation of street networks.

Climate change is a global phenomenon that exerts significant impacts on ecosystems. Estuaries, as critical aquatic habitats, are susceptible to these changes; however, our comprehension of their specific responses to climate change remains limited. Beyond temperature rise and alterations in precipitation patterns, climate change induces indirect effects, influencing a multitude of biotic and abiotic variables within aquatic ecosystems. In this study, we assess seagrass health as an indicator of estuary well-being in three estuaries located in northern to central California, USA. Our investigation focuses on the marine angiosperm Zostera marina (commonly known as eelgrass) and its associated parasite, Labyrinthula zosterae. Z. marina, a temperate marine plant, faces the threat of eelgrass wasting disease (EWD) caused by the protist L. zosterae. Notably, this pathogen demonstrates sensitivity to warming ocean temperatures, underscoring the imperative to comprehend its impacts on host health amidst climate change. Our study assessed EWD prevalence with relation to spatial and temporal patterns, the relationship, if any, between disease prevalence and eelgrass percent cover, the spatial patterns, if any, of eelgrass percent cover, and what climatic variables were most strongly correlated with EWD and eelgrass percent cover.

Microplastics have been detected as widespread in an aquatic environment at the microscale, also known as plastic debris. They have continuously increased due to the increase in population, production of synthetic plastics and poor waste management. They are ubiquitous and slowly degrade in soil and water. They are emerging contaminants that have received attention from research communities and public audiences over the last few years. They have high stability and can absorb several other pollutants like heavy metals, pesticides, etc. After entering the environment, they can accumulate and persist for a long time. They can create a serious threat to freshwater ecosystems and human health. These particles can cause physical damage to freshwater organisms. Raman spectroscopy, Fourier-transform infrared spectroscopy, visual identification, density separation, microscopic method, chemical method, thermos-analytical method and hyperspectral imaging method are the commonly known approaches for identification and quantification of microplastics. The noticed concentration of microplastics depends on the analysis method, sampling location and technique. The authors reviewed the sources, health impact, transport and treatment of microplastics in freshwater environments in detail. This study will provide the baseline data for the researchers to do more research on microplastic pollution in the future.

This study conducts a comprehensive analysis of the presence of heavy metals, including zinc (Zn), lead (Pb), copper (Cu), chromium (Cr), and arsenic (As), in the dust found inside educational buildings and the top layer of soil in different areas of Vilnius. The study focuses on the analysis of topsoil samples gathered between 2011 and 2023, with a specific emphasis on dust samples obtained from 24 schools in 2022. The research reveals significant variations in the concentrations of heavy metals, providing a clear understanding of the complex relationship between sources of urban pollution, environmental processes, and the correlation between soil and dust contamination by heavy metals. Indoor dust in schools shows unique contamination patterns in contrast to topsoil, suggesting distinctive sources of indoor pollution, while there are some general similarities. This finding emphasizes similarities and distinctions between soil and dust in educational environments. The study utilizes advanced statistical methods such as Pearson correlation, Principal Component Analysis (PCA), and hierarchical clustering to examine the distribution and characteristics of these metals. This study distinguishes itself by examining indoor dust in educational facilities and topsoil in Vilnius, providing crucial insights into the relationship between these two environmental matrices.

This paper presents the results of experiments on the study of a hydraulic fracture interaction with a preliminary created fracture that simulates a natural fracture. A distinctive feature of the conducted experiments is the ability to use an ultrasonic sounding to measure the fracture propagation and opening simultaneously with the fluid pore pressure measurements at the several points of the porous saturated sample. It allows to obtain the pressure distributions at various experiment stages and to establish a relation between the pore pressure distribution and the hydraulic fracture propagation and its interaction with macroscopic natural fracture. The possibilities of active ultrasonic monitoring have been expanded due to preliminary calibration experiments, which make it possible to estimate the fracture opening value by attenuation of ultrasonic pulses. The experiments show that the fracture propagation is limited by the natural fracture. This is caused by the hydraulic fracturing fluid leaks into the natural fracture, so both hydraulic fracture and natural fracture compose united hydraulic system.

Microplastic pollution is a serious global issue affecting freshwater systems, coastal regions, and oceans. These non-biodegradable materials have a detrimental impact on marine species and ecosystems, causing disruption to their feeding, breathing, and reproduction. In this study, 120 samples of two species of shrimp, P. monodon and P. indicus, from ten locations in the Negombo lagoon in Sri Lanka were analyzed. A total of 415 items were identified as microplastic with an average of 8.29 ± 4.63 items per gram in P. monodon and 5.52 ± 3.78 items per gram in P. indicus. The majority of microplastics identified were fibers (93%), and the remaining being fragments. Most of the microplastics were &gt;1000 μm, and the most prevalent color was blue (61%), followed by red (15%), black (9%), and others. These comprised of polystyrene, polyamide, polyester, polypropylene, and rayon, as identified by FTIR spectroscopy. This study highlights the prevalence of microplastics in shrimps harvested from the Negombo lagoon and the potential impact on marine life.

A high-resolution catalog for the 2014 Ms6.5 Ludian aftershocks was constructed based on the deep learning phase-picking model (CERP) and the seismic-phase association technology (PALM). A specific training strategy, which combines the advantages of the conventional short-long window average energy ratio algorithm (STA/LTA) and AI algorithm, is employed to retrain the CERP model. The P & S phases were accurately detected and picked on continuous seismic waveforms by the retained AI model. Hypoinverse and HypoDD were utilized for precise location of 3286 events. Compared to the previous results, our new catalog exhibits superior performances in terms of location accuracy and the number of aftershock events, thereby enabling a more de-tailed depiction of the deep-seated tectonic features. According to the distribution of aftershocks, it can be inferred that, (1) the seismogenic fault of Ludian earthquake is the NW-trending Baogunao-Xiaohe Fault. (2) the Ludian aftershocks interconnected the discontinuous NW-trending Baogunao-Xiaohe Fault, and intersected with the Zhaotong-Ludian Fault. (3) It suggests that the NE-trending Zhaotong-Ludian Fault may have been intersected by the NW-trending Baogunao -Xiaohe Fault, indicating that the Baogunao-Xiaohe Fault is likely a rela-tively young Neogene fault.

Large-scale farms are pivotal sites for the development of the agricultural industry, and the quality of the ecological environment is a significant factor affecting the growth of cereal crops. Consequently, assessing the ecological quality of large-scale farms is of great importance. This paper leverages the advantages of remote sensing imagery for long-term, quantitative, and dynamic monitoring of ecological quality over extensive areas. It develops an ecological assessment procedure suitable for agricultural regions based on an Improved Remote Sensing Ecological Index (IRSEI), which considers the coupling of ecosystem component elements. This procedure introduces a Pan-Salinity Index (PSI) tailored to the characteristics of soil salinization in farming areas and incorporates an ecological greenness index based on the Normalized Difference Vegetation Index (NDVI), an ecological humidity index derived from the K-T transform (WET), an ecological dryness index synthesized from the bare soil index and the built-up index (NDBSI), and an ecological heat index represented by the Land Surface Temperature (LST) calculated from atmospheric parameter models. These five indices are integrated into the ecological assessment system. The experimental results visually demonstrate the development and changes of ecological impact factors in the farm research area over the past decade, as well as the spatiotemporal variations in the quality of the farm's ecological environment. The findings indicate that between 2010 and 2019, the overall trend of IRSEI first declined, then rose, and subsequently experienced a slight decrease. Through differential analysis, regions and areas with declining ecological quality were identified, providing a data reference for the formulation and implementation of future ecological protection and management measures for the farm. The proposed IRSEI method offers a rapid and effective new monitoring approach for agricultural planting areas with a tendency towards soil salinization.

The purpose of this investigation was to study the impact of different rates of bio fertilizer on agronomic characteristics and the relations among herbaceous plant diversity and soil properties of Aloysia citrodora in central Greece. For this aim a two – year Completely Randomized Design (CRD) field experiment was carried out in central Greece. The experiments included four biological fertilizer levels, BF0: 0 kg ha-1, BF50: 50 kg ha-1, BF100: 100 kg ha-1 and BF150: 150 kg ha-1 with 3 replication. Plant height, dry stem, dry leaves, dry total yield and Leaf Area Ιndex (LAI) were measured during the two growing years. The results showed that in the 1st studied the maximum plant height was observed in BF150 treatment while the 2nd year the BF150 level provoked a raise of 16.08% and 1.09% compared to BF50 and BF100, respectively. The 1st year the values of total dry yield were better in BF150 application. The 2nd year the total yield increased by 50.27% in BF100 and 50.09% BF150 treatments. Moreover, LAI was ameliorated by applied the BF100 and BF150 treatments both in two studied years. A key finding in this study is that Aloysia citrodora ecosystem favors herbaceous plant species richness. Also, soil factors (soil organic matter, P and K) promote positive herbaceous plant diversity within the Aloysia citrodora ecosystem. Finally, Aloysia citrodora can be a promising medicinal plant, cultivated under the Mediterranean climatic conditions.

The previous studies on the diversion pipe of pumped storage power stations (PSPS) primarily focused on numerical simulations of pulsating pressure propagation within the pipe and its inducing factors. However, there was a lack of field monitoring and analysis of measured data to support surface ambient vibration, resulting in insufficient credibility and practicality of the numerical results. Based on ambient monitoring and data analysis, this paper examines the factors contributing to the ambient vibration of the water diversion pipeline in Changlongshan (CLS) PSPS. It is concluded that: (1) The primary source of vibration originates from units operation-induced ambient vibrations; (2) Vibration during pumping conditions exceeds that during power generation conditions; (3) The ground measuring point's vibration acceleration primarily depends on the distance from the vibration source; (4) Different types of units have varying effects on water diversion pipeline vibrations.

Effective development of digital twins of real-world objects requires sophisticated data collection techniques and algorithms for automated modeling of individual objects. In City Information Modeling (CIM) systems, individual buildings can be modeled automatically at the second Level Of Detail or LOD 2. Similarly, automated solutions for 3D modeling of individual trees at different levels of details are required for Tree Information Modeling (TIM) and building Forest Digital Twins (FDT). The existing algorithms support the automated modeling of trees by generating models of the canopy and the lower part of the trunk. Our work in this paper is based on the assumption that, similar to the canopy shape, the structure of tree trunk and branches is also an important consideration. An algorithm for automated modeling of tree trunks is proposed. Aiming to generate 3D models of tree trunks, the suggested approach starts by extracting the trunk point cloud, which is then segmented into single stems. Finally, the individual stems are modeled by dividing them into slices. The geometry of the developed tree models is represented in a matrix format. This solution enables automatic comparisons of tree elements over time, which is necessary for monitoring changes in forest stands and promoting sustainable forest management. Despite the huge variation of trunk geometric forms, the proposed modeling approach can gain an accuracy of better than 4 cm in the constructed tree trunk models.

Iron (Fe), the main component of non-exhaust particulates, is known to have variable health effects that depend on the chemical species of iron. This study characterized the possible contribution of iron oxides and hydroxides to airborne brake-wear particles under realistic vehicle driving and braking conditions with different brake-pad friction materials. We found significant differences in wear coefficients and PM₁₀ emissions between non-asbestos organics (NAO) and European performance (ECE) brake pads. Iron was the dominant contributor to PM₁₀ and PM_2.5 brake-wear particles for both NAO and ECE. The iron concentration ratio in the particle mass were comparable to the disc to pads ratio measured by wear mass. The fact that magnetite, which is of interest with respect to health effects, was less abundant in NAO than in ECE suggested that tribo-oxidations occurred in NAO. Metallic iron is generated not only from abrasive wear but also from tribo-chemical reduction with magnetite as the starting material. We found differences not only in PM emissions between brake friction materials but also that the phase transformations of iron differed between friction materials. These differences were apparent in the distribution of iron oxides and hydroxides. Heat, tribo-oxidation, and tribo-reduction are intricately involved in these reactions.

Carbonate rocks occupy about 6490 km2 in Albania (23% of the country) and the total exploitable karst water resources are estimated in 2.84*109 m3/year (about 65% of the total exploitable groundwater resources in the country, and about 70% of those used for water supply). In addition, karst massifs are very rich in thermal waters, related to the ascending fluids which are essential for the development of hypogenic karstification in the outer Albanides. This type of karst facilitates the circulation regime of deep fluids, which are revealed at the surface through both numerous phenomena of hypogene karst and hot springs. The relatively small Kruja Tectonic Zone is characterized by the presence of SE-NW oriented carbonate structures, rich in thermal sources, and contains more than the 80% of Albania thermal springs. One of its most interesting carbonate structures, for the presence of both cold and thermal waters, is the small karst structure of Makaresh, with a surface of 22 km2. The purpose of this article is to describe the characteristics and factors that affect the quantitative and qualitative formation of cold and thermal groundwater in this massif. Based on the physico-chemical characteristics, groundwaters of the study area are classified in cold and thermal waters. The former are mainly of HCO3-Ca or HCO3-Ca-Mg type (Electrical Conductivity 580-650 μS/cm, Temperature 13.9-16.6° C). Thermal waters are mainly of the Cl-Na-Ca type (EC 7200-7800 μS/cm, T 18.5-22.5° C); further, they are characterized by high hydrogen sulphide concentration, up to about 350 mg/l. The presence of two groundwater types in the Makaresh massif is connected to the presence of two groundwater circulation systems. The main factors of the groundwater physic-chemical quality are the solution of rocks and minerals therein contained, the presence of hypogenic speleogenesis, and the mixing of the groundwater of the two systems. The hydrogeological studies proved that karst rocks contain considerable fresh water resources; the capacity of water wells used for the drinking water supply reaches up to about 50 l/s. Thermal waters are not currently exploited due to their temperature, but they are potentially suitable for thermal uses, by drilling boreholes at depth of about 1000 m.

In order to analyze the spatial distribution characteristics of the cultural landscape of the Yangtze River (Nanjing section) and show the role of the Yangtze River culture in promoting regional economic development and cultural radiation, Based on the Knowledge graph technology and 3S technology, this paper conducts geographical positioning and spatial analysis of the Yangtze River cultural landscape in Nanjing, and analyzes the surrounding environment by combining remote sensing images and topographic data. Researches show that: The Yangtze River cultural landscape in Nanjing includes 74 landscape points of seven landscape types, and the distribution of landscape points shows a clustering trend, but the spatial distribution and aggregation degree of different types of cultural landscapes are different. Due to the influence of climate environment and water resources distribution, the surrounding cultural landscape has a low altitude and high vegetation coverage, showing obvious distribution characteristics along the river. This study is helpful to improve the coordination degree between cultural landscape protection and planning management, and can provide useful reference for the protection of cultural landscape of the Yangtze River.

Methane is a greenhouse gas and identified as a key driver of near-term climate change. Bottom-up approaches estimate annual methane loss from US natural gas production and transport at 6 Tg, but recent studies suggest this may be an underestimate. To investigate this possibility, an equipment-based emissions inventory, using EPA emission factors, was developed to calculate methane emissions from oil and gas operations in the Delaware Basin, USA. Emission factors and activity data were then updated using contemporary and region-specific measurement data. The original inventory estimated emissions at 315 Gg CH4 y-1 (gas production-normalized rate of 0.6% loss), while the updated inventory estimated emissions of 1,500 Gg CH4 y-1 (2.8% loss). The largest changes resulted from large fugitive emissions from oil production (+430 Gg CH4 y-1), updating maintenance activity emissions (+214 Gg CH4 y-1), considering flaring inefficiency (+174 Gg CH4 y-1), and the inclusion of associated gas venting (+136 Gg CH4 y-1). This study suggests that a systematic underestimate probably exists in current bottom-up inventories and identifies sources currently missing or may be incorrect. We also strongly recommend that emission factors should be validated through direct comparison against measurement campaigns that include long-tail distributions typical of oil and gas activities.

To meet the International Maritime Organization’s requirements for carbon dioxide emissions from ships, a cost-effective and practical ship decarbonization tower was autonomously designed based on the marine diesel engine model 6135G128ZCa. The tower is internally filled with structured packing, and a slot-type liquid distributor at the top of the packing evenly distributes the NaOH solution to absorb carbon dioxide from the ship’s exhaust gas. Experimental research was conducted to investigate the influence of factors such as liquid-to-gas ratio and NaOH concentration on the performance of the decarbonization tower. The results confirmed that the use of NaOH solution can effectively absorb CO2 from ship exhaust gas, reducing CO2 emissions by more than 81.59% and meeting the EEDI (Energy Efficiency Design Index) requirements specified by the IMO.

X-band marine radar captures signal reflected from the sea surface. Theoretical studies indicate that the initial unfiltered signal contains meaningful information including parameters related to wind waves. Traditional methods for estimating significant wave height (SWH) rely on the physical laws describing signal reflection from rough surfaces. However, recent studies suggest the feasibility of employing artificial neural networks (ANNs) for SWH approximation. Both classical and ANN-based approaches necessitate costly in situ data. In this study, we propose generating synthetic radar images with specified wind wave parameters using Fourier-based approach and Pierson–Moskowitz wave spectrum as a viable alternative. We generate synthetic images and use them for unsupervised learning approach to train a convolutional component of an ANN. After that, we train a regression ANN based on the previous convolutional component to obtain SWH back from synthetic images. Then, we apply preliminary trained weights for the same regression model to train SWH approximation on the dataset of real sea clutter images. In this study, we demonstrate the increase in the accuracy of SWH estimation from radar images with the preliminary training on synthetic data.

Cacao (Theobroma cacao L.) is an important woody species for production in Ecuador. Woody species have the potential to incorporate soil organic carbon (SOC) into the soil. The province of Manabí is known for its cocoa plantations and several cocoa species, which generates interest in their analysis. This study aimed to determine the concentration and accumulation of SOC in three cocoa species (EET95, EET103 and EET116) 15 years old, both under the tree and in the rows, at different depths 0-5, 5-10, 10-20 and 20-30 (cm). The results showed that soil SOC concentration was higher in the row for EET116 (2.51%) and significantly different under the tree for EET103 (1.57%) at 0-5 cm. No significant differences were found in the other sections. In the whole profile analyzed (0-30 cm), the EET116 species accumulated 41 t ha-1 and 54 t ha-1 under the tree and in the row, respectively. The species EET103 in the row presented 47 t ha-1 with no significant differences. Species EET95 and EET103 had the lowest values, but without significant differences between sampling locations, with 36 t ha-1, 37 t ha-1, and 47 t ha-1 under the tree and in the windrow, respectively. In conclusion, the species EET116 accumulated more organic carbon due to several factors, possibly a higher decomposing biomass, not only from the tree but also from other trees in the area, which contributes to the incorporation of organic matter throughout the soil profile.

Abstract: To explore the interrelationship between groundwater microbial communities and hydrochemical characteristics in Mancheng district, Baoding city, samples from karst groundwater and porous groundwater were collected respectively. The hydrochemical analysis and 16s RNA gene V4-V5 region sequencing method were used to detail the water environmental characteristics and microbial community distribution pattern in the study area. The hydrochemical results reveal significant differences in major ion contents and other hydrochemical indices between karst water and porous water. Microbial community analysis demonstrates that Proteobacteria, Actinobacteria, and Firmicutes are the dominant taxa in both types of water bodies, but their proportions vary significantly in different water bodies. The difference in microbial communities between karst water and porous water reflects the influence of environmental factors such as ion concentration and pH on microbial distribution. Redundancy analysis (RDA) indicates significant associations between microbial community composition and environmental factors in both types of groundwater environments. Studying the distribution pattern of microbial communities and the connection with environmental factors in two types of groundwater provides important basis for interpreting the functional roles of microbes in groundwater ecosystems.

Carbon (C) is one of the most abundant elements. It is part of all living organisms and is found in all states of matter (solid, liquid, gas, and plasma). It can take the form of one of the hardest and transparent materials (diamond) or it can be flexible and dark ( graphite), with many carbonaceous materials at both extremes. In gaseous form, C is a component of several greenhouse gas emitted during the combustion of fossil fuels. Carbon movement between the atmosphere, land (biosphere and lithosphere), and ocean (hydrosphere) can alter total amounts in each pool. Human activities accelerate C movement into the atmosphere, causing increases in climate change. This shift from terrestrial and oceanic C pools to the atmosphere cause an increase in the intensity and duration of droughts, hurricanes, snowstorms, and other natural phenomenon. Although society hears about C emissions there is a lack of understanding of its importance and the need to decrease C in the atmospheric pool to avoid exacerbating climate change. Forests and biochar are two biological methods to retain C in the terrestrial pool for long time and at very low cost. This review details where C comes from, its relationship with forests, and biochar and their roles in increasing carbon sequestration to limit the impacts of climate change and continue having future sustainable forests and ecosystems services that we enjoy today.

The urban planning transformations modify the morphological shape of the territory changing land uses and permeability of the areas involved in the evolution processes, thus also altering the hydrologic responses to climatic events, namely the urban drainage runoffs that impact on the environmental risk of modern cities. Using the watershed hydrologic concept, in its dynamic evolution, it is possible to consider the morphological layout together with the transformations implemented by the human activities and any different territorial portions could be analyzed in connection with the other areas related by the dynamics of the surface runoff, thus highlighting the reciprocal influences between the different areas. By examining the morphological shapes impacting surface outflows, the hydrological roles of upper-mountain, intermediate-hillside, and lower-valley areas reveal urban and non-urban connections. This elucidates hydromorphic complexities in urban transformations and assesses climate change adaptability. The proposed approach has been applied to the urban district of “Sasso Caveoso”, belonging to the city of Matera and consents to quantitatively synthesize the response of the context analyzed, referring to different scenarios and providing useful decision support tools.

Cirrus thinning, as one kind of geoengineering approach, not only cools our planet but also enhances the amount of sunlight reaching Earth's surface (brightening effect). This study delves into the brightening effect induced by cirrus thinning with a flexible seeding method. The thinning of only cirrus clouds results in a considerable globally averaged cooling effect (−2.46 W m−2), along with a notable globally averaged brightening effect (2.19 W m−2). Cirrus thinning also results in substantial reductions in the cloud radiative effects of the lower mixed-phase and liquid clouds. While these reductions counteract the cooling effect from cirrus clouds, they enhance the brightening effect from cirrus clouds. Consequently, the brightening effect caused by cirrus seeding (4.69 W m−2) is considerably more potent than its cooling effect (−1.21 W m−2). Furthermore, due to the more pronounced changes from the mixed-phase and liquid clouds at low- and mid-latitudes, the cooling effect is primarily concentrated at high latitudes. In contrast, the brightening effect is significantly stronger over most low- and mid-latitude regions. Overall, cirrus thinning could lead to a notable brightening effect, which can be leveraged to offset the dimming effect (the opposite of brightening effect) of other geoengineering approaches.

Water pollution, intensified by the release of hard-to-degrade pollutants, poses severe threats to ecosystems, human health, and economic development. The existing advanced oxidation processes often involve high operational costs and may result in secondary pollution, highlighting the necessity for innovative and more sustainable solutions. To address these challenges, our study introduces a cost-effective and eco-friendly corona discharge barrier plasma discharger for wastewater treatment. Through the central composite design/response surface methodology, a high decolorization rate of 98% of methylene blue (MB) within 10 minutes was achieved by optimizing parameters such as pH and voltage. Furthermore, the mechanisms of the generation of reactive oxygen species via this device was discussed in detail and the degradation pathways of MB were described. Moreover, this device is also very energy-efficient, with a low energy density and electrical energy per order of 0.15 watt/mL and 5.79 kWh/m³/order, respectively. In conclusion, the plasma discharger developed in this study provides a cost-effective and environmentally sustainable solution for dye wastewater treatment. This research contributes significantly to the advancement of sustainable dye wastewater management practices, offering an innovative method that meets both environmental and economic objectives.

The retrieval of tree height percentiles with satellite lidar waveforms over the mountainous ar-eas is greatly challenged due to slanted and rugged topographic relief of underlying ground. A novel algorithm is proposed to extract the height percentiles based on the target response waveform (TRW) that is resolved by using a Richardson–Lucy deconvolution algorithm with an adaptive iterative time. The height metrics of the energy percentiles of 25%, 50%, 75% and 95% for the cumulative TRW distribution are determined by their vertical distances relative to the ground elevation in this study. To validate the proposed algorithm, we select the received waveforms of the Global Ecosystem Dynamics Investigation (GEDI) lidar over the Pahvant Mountains of central Utah, USA. The results reveal that the resolved TRWs resemble closely to the actual target response waveforms from the coincident airborne lidar data, with the mean values of the coefficient of correlation, total bias and root mean square error (RMSE) taking val-ue of 0.92, 0.0813 and 0.0016. In addition, the accuracies of the derived height percentiles from the proposed algorithm have been greatly improved compared with the conventional Gaussian de-composition method and the slope-adaptive waveform metrics method. The RMSE values de-crease by the mean values of 1.96 m and 2.72 m, respectively. It demonstrates that the proposed algorithm has good potential in the extraction of forest structure parameter over rugged moun-tainous areas.

Greenhouse gases (GHGs) trap heat in the atmosphere, causing the Earth's surface temperature to rise. The main GHGs are carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), perfluorocarbons (PFCs), hydrofluorocarbons (HFCs), and sulfur hexafluoride (SF6). Human activities are increasing GHG concentrations rapidly, which is causing global climate change. Global climate change is increasing environmental and public health problems. To reduce greenhouse gas (GHG) emissions, identify where the emissions are coming from, develop a plan to reduce them, and then implement and monitor the plan to ensure that emissions are actually reduced. Anthropogenic global climate change has large and increasingly adverse economic effects. Cities emit the most GHGs due to fossil fuel burning and power usage. The four major GHG emitters are energy, transportation, waste management, and urban land use sectors. Organizations should prepare action plans to lower their GHG emissions and stop the worst consequences of climate change. These action plans require companies and local authorities to submit their GHG emissions reports on a yearly basis. A GHG emissions management system includes several processes and tools created by organizations to understand, measure, monitor, report, and validate their GHG emissions. Two of the most widely adapted frameworks for GHG inventory reporting are ISO 14064 and the GHG Protocol. This review paper aims to identify some of the key points of GHG inventory preparation and mitigation strategies.

High levels of groundwater containing both arsenic and fluorine are prevalent, resulting in serious health problems when consumed as drinking water. This co-pollution phenomenon is widespread and requires urgent attention. The multiple forms of arsenic and arsenic-fluorine co-contamination pose a significant challenge to efficiently co-remove both substances. This research utilized a green and stable synthesis approach to create MgLaFe LDO heterostructures, which were anchored on α-MnO2 nanowires. The materials comprise magnesium and lanthanum elements with a powerful attraction towards fluoride ions, elemental iron, which can establish stable compounds with arsenate, and MnO2, which can effectively oxidize arsenous acid, thereby enabling efficient co-removal of arsenic and fluorine. The efficient oxidation process of the MnO2 nanowire and the prompt ion adsorption process of the LDO work together synergistically. The adsorption performance was assessed through isotherm and kinetic fitting. Chemisorption was found to be the process for As(Ⅲ), As(V), and F- adsorption, with As(Ⅲ) going through monolayer adsorption on the surface of MnO2 nanowires, while As(V) and F- were mainly adsorbed by multilayer process on LDO. The maximum adsorption capacities were 111.76 mg/g, 230.51 mg/g, and 765.10 mg/g for As(Ⅲ), As(V), and F-, respectively. The XPS analysis provided further elucidation on the adsorption mechanism of the MnO2@LDO heterostructure, detailing each component's role in the process. The results confirm the successful construction of the heterostructure and its efficient coupling of oxidation and adsorption.